Indian Journal of Pharmaceutical Education The Official Journal of Association of Pharmaceutical Teachers of India (Registered under Registration of Societies Act XXI of 1860 No. 122 of 1966- 1967, Lucknow) Web Site - www.ijpe.org ISSN - 0019 - 5464 e-mail : [email protected] Abstracted in International Pharmaceutical Abstract Vol. 39(5)* Editor B.G. Nagavi, Ph.D. Mysore. 1997 - till date Number 02 Invited Editorial 60 61 P. Gundurao, Ph.D. Manipal. 1985-1995 A.V. Kasture, Ph.D. Nagpur. Jan 1981 - Jun 1984 Restructuring Pharmacognosy in Emerging Global Scenario - P.Velayudha Panicker Letter to the Editor Past Editors M.N.A. Rao, Ph.D. Manipal. 1995-1996 April - June 2005 Pharmacy Education in India - U.B. Hadkar Tutorial Review 62 Insights into Artificial Neural Networks and its implications for Pharmacy – a Tutorial Review: Part - 3 - Sathyanarayana Dondeti, K. Kannan and R. Manavalan Review Article 71 Emerging Challenge of Herb-Drug Interaction - U. N. Harle, N. J. Gaikwad Articles 82 Need of Upgradation of Diploma in Pharmacy Curriculum - Mehta Nikhil K, Asnani Alpana, Pathak Ajay V and Rabra Vandana A.N. Saoji, Ph.D. Nagpur. March 1980 - Dec 1980 85 Study of the Dimer of Imipramine Radical as Laboratory Marker for Antioxidant Evaluation - M.K. Tripathy, D.K. Tripathi and U.N. Dash 89 Leveraging through Marketing in Modern Times - Manthan J., Udupa N C.L. Lakhotiya, Ph.D. Nagpur. Jan 1979 - Jan 1980 92 Ribozymes: The Trans Acting Tools for RNA Manipulation - A. Nayak, and D. V. Kohli 97 Microwave Assisted Rapid Quantitative Analysis of Aspirin, Calcium Carbonate & Riboflavin - Shrishailappa Badami, Natasha Joseph Chelapureth, Deepa S, Sandhya Deepa E, Elna Merilla Bose, Vijeesh Govindan and Suresh B 100 Institutional Excellence – An Approach to Contend in Global World - A. M. Godbole and S. A. Sreenivas 103 CoMFA-A 3D QSAR Approach and its Applications - Sanmati K. Jain 108 Spectrometric Method for Determination of Carbocysteine - P. N. Sanjay Pai, Gopalkrishna Rao, B. Balakrishna, Hamid Khan and K. Pasha C.T. Chopde, Ph.D Nagpur. Sept 1978 - Dec 1978 P. Gundurao, Ph.D. Manipal. 1975 - 1978 B.M. Mithal, Ph.D. Pilani. 1967 - 1974 Ph.D Thesis 110 Study of anti-ulcer activity of some herbal drugs - Siddhraj Singh Sisodia 112 Book Review Indian J.Pharm. Educ. 39(2) April - June 2005 57 * Number in bracket indicates the new number after registration of IJPE with registrar of news papers for India , New Delhi. Invited Editorial Restructuring Pharmacognosy in Emerging Global Scenario P.Velayudha Panicker Professor of Pharmacognosy (Retd), Chalayil, Kavalam 688 506 Received on 17.01.2005 From the present status, Pharmacognosy has a greater task to perform in the emerging scenario of fulfilling the social need of health care system of India 2020 A.D. Being a part of the clan since 1958, except for phytochemistry and synthetic pharmaceutical chemistry contributing a great deal to industry, I am not yet convinced how far has a Clinical pharmacist achieved any significant triumph from social point of view as an inevitable unit in hospital scenario. The opinion that is being conveyed here is an extension of my article ‘Herbal pharmacist-a link between tradition and modernity’ published in IJPE in 2002, to explore the role of a herbal pharmacist in hospital environment as distinctive and individualistic from the design and working of a phytochemist and propose a restructuring process of pharmacognosy curriculum at least in post-graduate level. An herbal pharmacist is to be trained in traditional formulations [Ayurveda, Unani or Sidha depending on regional needs] in the P.G. level overcome these hurdles to practice their traditional ‘YingYang’ concept under the same roof of modern therapy. I believe that as a branch of science of longevity, Ayurveda formulate a recipe only after diagnosis from patient counseling and this is synonymous to Dispensing practice of yesteryears. A market product of Ayurveda was hardly available about a century back. Ayurveda training even today advocates flexible combination or formulation decided on the conclusion of physician after diagnosis of patient. The reason for this, on one side is its basic principle of patient oriented holistic outlook and on the other side, the difficulty in procuring genuine raw materials leading to finished products of uniform standards. Looking from another angle, many modern practitioners look down the traditional systems with aversion and brush aside as unscientific. A molecular level of activity need not always be insisted; instead the efficacy of multiple components if proved; shall be to devise quality control of raw materials, finished products and improvise preparative technique in collaboration with traditional physicians in hospitals. The accepted and documented even forgetting the chemistry syllabus has to be accordingly designed so that the herbal pharmacist has to act as a link between traditional and modern physicians. systems [at least in private hospitals] co-exist and codify I have had occasion to witness in many places in South India-especially in Kerala where many Ayurvedic Vaidyasala simultaneously maintains practice of modern through modern physicians. Herbal pharmacist has a medicine. It is also true that a number of modern private hospitals do practice a holistic traditional system side by side. But there again, they do not have a common meeting molecular level taking priority area to continue prevailing place to exchange and interact the end result in a scientific way of documentation. This is where a herbal pharmacist can play a role in a creative way to develop formulation technique in tune with bedside patient counseling. There are some unsympathetic hurdles that may come on the way to make this rendezvous of two systems difficult. The Chinese however to a certain extent have 60 of molecules. These hurdles can be surpassed only if both the the documentation of clinical data of such modified traditional formulations to bring out clinical results crucial role in linking these systems. Further, it encourages a phytochemist to work on herbal drugs in phytochemical research program of Pharmacognosy. The opinion expressed is the continuation of my endeavour to bring the attention of academicians and pharmacognosists to justify the history of Indian pharmacy and the urgency in preserving the vast wealth in treatise in proper perceptive of global context without which there is no rationale in writing history of Indian pharmacy and therapy. Indian J.Pharm. Educ. 39(2) April - June 2005 Letter to the Editor Pharmacy Education in India U.B. Hadkar Mumbai Education Trust’s Institute of pharmacy, Bandra(W), Mumbai 400 050 Received on 01.03.2005 I wish to congratulate Mr. Shantanu Kale for his excellent article on pharmacy education. He was bold enough to state problems arising out of the two statutory bodies: Pharmacy Council of India and All India Council for Technical Education. He has correctly pointed out the consequences that would result if the D. Pharm course is closed down. The AICTE, the PCI, University and the state governments hold inspection of teaching institutions for the approval, the extension of approval and affiliation and extension of affiliation and this takes a lot of time in completing the formalities. I have to make a suggestion in this regard. The above stated authorities should evolve a common format for the inspection and should send the inspection committee comprising of representative of each one of the authorities so that there is no loss of time in conducting separate inspections. This will enormously cut down the unnecessary paper work and the college administrators will be greatly relieved. As per the existing norms & standards laid down by the AICTE, and PCI, the teaching institutions have to invest lacs of rupees on buying the journals as well as costly instruments. Effort should be made to have a centralized building in each of the cities like Mumbai, Kolkata, Chennai etc., having all the costly instruments, Indian J.Pharm. Educ. 39(2) April - June 2005 such as NMR, FTIR, HPLC etc., and also a centralized library should be housed in the same building having the collection of various journals-national and international. The funds necessary for raising such a centralized building and for the maintenance of the same may be collected from the various pharmacy colleges in the city or in that state. This will considerably reduce the financial burden on the pharmacy colleges and will save foreign exchange. The colleges can have the e-library facility so that the teachers & students can have access to different journals in the college library. This will also minimize the requirements of space to be allotted towards such facilities in individual institutions. The centralized library can also have the internet facilities and the elibrary. The students and teachers who use the facilities may also be charged a nominal fee per year OR the modalities may be worked out. I hope that office bearers of AICTE, PCI, University and Government offices start thinking on the above lines and each city will have a centralized building for instrumentation and library. I appeal to different associations like Association of Pharmacy Teachers of India, office bearers of AICTE & PCI to give a serious thought to my above suggestions. 61 Pharm. Education Tutorial Review Insights into Artificial Neural Networks and its implications for Pharmacy – a Tutorial Review: Part-3 Sathyanarayana Dondeti* , K. Kannan and R. Manavalan Received on 19.6.2004 Department of Pharmacy, Annamalai University, Annamalainagar 608 002 Accepted on 25.11.2004 Scope In this third part of the tutorial review series some typical problems relevant to pharmacy have been chosen for discussion to provide some insights and at the same time to serve as a pointer to the implications of neural networks as relevant to pharmaceutical scientists. A brief survey of relevant applications from scientific literature is presented at the appropriate juncture to enable interested readers to dig deeper in their respective field of application. The next and final part of the series would encompass data processing, performance evaluation, some essential mathematics and other paraphernalia in handling neural networks. Drug Analysis ANNs can be used to build empirical multivariate calibration models for the simultaneous estimation of multi-component formulation by spectrophotometry. Absorbance values, at a series of selected wavelengths, of a solution containing the analytes as multivariate input and the corresponding concentrations of the analyte as the target forms a training pair. The training pairs of a large number of solutions containing varied proportions of the analytes form a training set (or calibration set). Training set for calibration can be generated experimentally with reference methods such as the wet chemistry or obtained from synthetic mixtures prepared from standard solutions with known concentrations. The input layer and output layer contains neurons corresponding to the number of wavelength points selected and the number of analytes in the sample respectively. The ANN may contain one or more hidden layer with or without bias depending upon the problem at hand. The flexibility of ANNs and their ability to maintain their performance even in the presence of significant amounts of noise in the input data are highly desirable 1, 2, since perfectly linear and noise free data sets are seldom available in practice, thus making it suitable for multivariate calibration modeling. The authors have published their studies on the application of ANN for multi-component sample analysis 3, 4, 4a, 4b. Simultaneous determination of multi-components of six amino acids using a linear neural network (LNN) algorithm is reported by Yin 5 et al. They selected 17 wavelength points from the original UV spectral data with 343 wave length points (193.85 to 296.45nm with 0.3nm interval) as input for the LNN to build a neural network model with accurate results as evidenced by split-sample validation and leave-one-out cross validation. Simultaneous quantitative estimation of acetaminophen and phenobarbital in pharmaceutical preparations was done with kinetic spectrophotometric data using three models namely, ANN, ANN coupled 62 with principal component analysis (a method for dimension reduction) (PC-ANN) and partial least squares (PLS) models was reported by Ni6 et al. The method relies on the different kinetic rates of the analytes in their oxidative coupling reaction with 3-methylbenzothiazolin2-one hydrazone (MBTH) in the presence of hydrochloric acid and the Fe(III) oxidant. The absorbance was measured and recorded from 440 to 740 nm every 60 seconds from 15 to 435 seconds. The performance of the various models was compared with a validation set of overlapping spectra containing kinetic data of binary mixtures with different concentration ratios of acetaminophen and phenobarbital. Investigation of these models with simulated data and validation measurements from synthetic binary mixtures of the analytes showed that PC-ANN is a more effective calibration method with better prediction (lower relative prediction error [RPE]). PC-ANN was found to be the most efficient of the three models since it not only simplifies the training procedure of the ANN but decreases the contribution of experimental noise and other minor extraneous factors due to the inclusion of only the significant principal components in the model. Prediction of drug content and hardness of intact tablets using ANNs and Near Infrared spectroscopy has been reported by Chen7 and his co-workers. Duponchel8 et al, have developed a neural network approach to correct for spectral differences between two spectrometers. Spectral response of a given instrument is modeled from another before the use of the calibration equations. In this way, the time-consuming step of recalibration for the second spectrometer is avoided and the initial error prediction level is retrieved. Pharmacokinetics Population Pharmacokinetic Data: Applicability of using a neural network approach to analyze population pharmacokinetic data was reported by Chow9 et al. Data * For Correspondence. Indian J.Pharm. Educ. 39(2) April - June 2005 were collected retrospectively from pediatric patients who had received tobramycin for the treatment of bacterial infection. The information collected included patientrelated demographic variables (age, weight, gender, and other underlying illness), the individual’s dosing regimens (dose and dosing interval), time of blood drawn, and the resulting tobramycin concentration. This network had seven input variables (i.e., age, gender, illness, weight, dose, dosing interval, and time of blood drawn). The values of age, weight, dose, dosing interval, or time of blood drawn were normalized linearly to range between 0 and 1. Gender and illness variables had values of 0 or 1, with male 0, female 1 and oncology 0, cystic fibrosis 1, respectively. The logarithm of the tobramycin concentration was used as output values, which were normalized to result in output values ranging from 0 to 1. After experimentation, eight and seven hidden nodes were selected to provide the interconnections between input and output for neural networks test I and test II, respectively. Seven hidden nodes were found to be optimum. Each node in a layer is connected to every node in the next layer. Each of the 622 patients’ clinical information, tobramycin dosing regimens, and time of blood drawn along with corresponding tobramycin concentration measurements was treated as input and output data pair. The network training started with a random set of connection weights. The delta rule 10 was used as the error correction formula to adjust the connection weights each time the network saw a new input-output pair. The method suggested by Rumelhart 11 was adopted to incorporate a tuning (or validation) data set to prevent generalization problems. Convergence of training (termination of training) was determined when the network showed a minimum sum of square error in predicting the tobramycin concentrations in the tuning data set. This work showed that neural networks were capable of capturing the relationships between patientrelated factors and plasma drug levels from routinely collected sparse within-patient pharmacokinetic data. This further documents the applicability of neural networks to population pharmacokinetic data analysis. Prediction of Plasma Levels of Amino glycoside Antibiotic: Prediction of plasma peak and trough levels of an amino glycoside antibiotic in patients with severe illness in an intensive care unit by a novel approach was reported by Nishizawa 12 et al. Knowledge of the pharmacokinetic (PK) and pharmacodynamic PD parameters is helpful for selecting the initial dosage regimen and subsequent adjustment of drug dosage. However, because the PK and PD characteristics of these patients may be far from the normal physiological condition, it is difficult to predict or to estimate the PK and PD parameters. If plasma levels of drugs in these patients could be predicted from selected physiological Indian J.Pharm. Educ. 39(2) April - June 2005 measures, it would be of great assistance in determining the appropriate dosage regimen without the need for the determination of blood concentration experimentally. Plasma levels were predicted based on the values of 15 physiological measurements using an artificial neural network (ANN) simulator. Physiological measurements were collected for 30 patients who were given Arbekacin sulfate (ABK) 100 mg of ABK was administered by intravenous drip infusion for one hour in each 12 hour period. Blood samples were taken from the patients just after administration (peak level) and just before the next administration (trough level). The concentration of ABK in plasma was determined by a fluorescence polarization immunoassay. The following 15 physiological measurements were collected for each patient: age, body weight, rectal temperature, mean arterial pressure, heart rate, respiratory rate, arterial pH, serum sodium concentration, serum potassium concentration, serum creatinine concentration, hematocrit, white blood cell count, volume of parenteral fluid, volume of urine and C Reactive Protein (CRP). A data set of 15 physiological measurements for 30 patients was used to develop the model. The ANN structure consisted of three layers: an input layer comprised of 15 processing elements (necessarily same as the number of variables), a hidden layer comprised of 10 processing elements with a sigmoid function as an activation function, and an output layer of two processing elements (peak and trough levels). One additional “bias” neuron was incorporated to act on the hidden and output layers. The ANN was trained according to the delta rule back-propagation using “error backpropagation learning”13. The training of the network was stopped when the maximum error between observed and predicted values had decreased to a value less than 0.01. The network had been trained 10 times, each time using new random sets of initial weights. The goodness fit was evaluated by root of mean squared error (RMSE). The correlation coefficients between observed and predicted values obtained by ANN prediction using standardized data sets were r = 0.825 and r = 0.854 for peak and trough levels, respectively. These results indicate that ANN shows better performance in prediction of amino glycoside antibiotic plasma levels from patients’ physiological measurements than MLRA. Prediction of plasma levels of antibiotic in patients with severe illness by ANN was superior to the standard statistical method. Standardization of input data was found to be important for better prediction. ANN has some advantages over standard statistical methods, as it can recognize complex relationships in the data. Similarly Yamamura 14 has demonstrated the superiority of ANN over multiple regression analysis in predicting the plasma concentration of aminoglycosides (arbekacin sulfate and amikacin sulfate) in severely ill 63 patients by. In this study plasma level was predicted by ANN model using parameters related to the severity of patient’s condition. Gentamicin peak predictions: Gentamicin peak predictions were made using neural network model by Smith and Brier15. Peak observations from 392 patients were used to train, test, and validate the feedforward neural network. Inputs were demographic and drug dosing information. Data were collected from dosing records on 392 patients that received Gentamicin and had the pharmacy follow drug dosing. Information on patient age, height, weight, serum creatinine and gender were recoded from which creatinine clearance, body surface area and ideal body weight were calculated. The dose of Gentamicin received, dose interval, and the subsequent steady-state peak and trough were also recorded. The total data set was subdivided randomly into three sets. The first set consisted of 200 records and was used as training set. The second data set was termed the testing data set and was used to periodically test the predictive performance of the model and consisted of 92 records; the final data set consisted of 100 records and was used to validate the predictive model. They concluded that neural networks can be built using large number of parameters that have good predictive performance. Pharmacokinetic-Pharmacodynamic model: A novel model-independent approach to analyze pharmacokinetic (PK) and pharmacodynamic (PD) data using ANNs has been reported by Gobburu 16 and his co-workers using simulated data with standard mathematical relations governing the PK and PD of hypothetical drugs. The dose, time and logarithm of drug concentration served as input variables and PD effect as the output variable with two hidden layer neurons. The prediction quality of a network was assessed by employing the correlation coefficient between the output and desired (target) as the numerical performance index. The pharmacological effect was assumed to be free of any contributions from an active metabolite. The trained network was used to predict the PD effect at a higher dose. Similar tests were conducted when the drug was administered extravascularly and in another instance when the drug was given an intravascular injection. ANNs were found to be successful in predicting the PD profiles accurately in both cases. Quantitative Structure-Pharmacokinetic Relationships (QSPR): The application of neural networks to predict the pharmacokinetic properties of beta blockers in human has been reported by Gobburu and Shelver17. The beta blockers included in their study were acebutolol, alprenolol, atenolol, bufuralol, metoprolol, nadolol, pindolol, propranolol, timolol and tolamolol. The pharmacokinetic parameters (targets) studied include 64 fraction drug bound plasma (fb), steady-state volume of distribution based on the total drug in plasma (Vss), steady-state volume of distribution based on the unbound drug in plasma (Vuss), renal clearance (CLr), non renal clearances (CLnr), and mean residence time (MRT). Table 1: Input and Output Parameter for the Neural network Output Parameters Input Parameters Logarithm of Fraction bound pK a and logarithm of Ksf Volume of Distribution pK a and logarithm of Ksf Logarithm of Renal Clearance Logarithm of Ksf and logarithm of fb Logarithm of Non-renal Clearance Mean Residence Time pK a and Ksf pK a and Ksf As predictor (input) variables, they used pK a , octanol/buffer (pH 7.4) partition coefficient determined by the shake flask method (Ksf), and the fraction of the drug bound in plasma (fb). A separate neural network was developed for prediction of each of the pharmacokinetic parameter. Table 1 illustrates the data sets used for prediction of various pharmacokinetic parameters. In all cases five hidden neurons were used. The neural network-predicted values showed better agreement with the experimental values (8% mean difference) than those predicted by multiple regression techniques (47% mean difference). Intestinal absorption prediction: A three layer, feed forward neural network has been developed for the prediction of human intestinal absorption (HIA%) of drug compounds from their molecular structure 18. The data set contained 86 drug and drug-like compounds whose molecular structure was described with six descriptors. This model does not produce an exact rank ordering, but is clearly differentiates the well absorbed compounds from the poorly absorbed ones and thus illustrates the potential of using QSPR methods to aid drug development process. QSAR Applications QSAR of Carboquinones: Aoyatoma 19, 20 et al. chose a data set that had previously been studied by Yoshimoto21 et al. using traditional modeling techniques such as MLRA in order to compare those results with the results of neural networks The QSAR relationship study was designed to predict the minimum dose of drug (carboquinone and its analogues) required to produce a 40% extension of the lives of test animals (mice) that had been inoculated with lymphoid leukemia L-1210 cells. This minimum effect dose depends on the concentration, C, Indian J.Pharm. Educ. 39(2) April - June 2005 of the substance necessary to give the desired effect, and is given as log(1/C). The more effective the drug is, the smaller will be the concentration necessary. Since the required concentration of different drugs vary over several orders of magnitude, log (1/C) (the logarithmic transformation) has been chosen as a measure of effective dose. Altogether 35 different carboquinones were selected; for all of them, a total six variables were used as inputs. The variables (four) describing the combined influence of substituents are molar refractivity, contribution to hydrophobicity, sum of the constants for field effect and sum of the constants for resonance effect. The variables describing the influence of one substituent include the molar refractivity and the contribution to hydrophobicity. The output consisted of the minimum effective dose which is given by log (1/C). Thus the neural network consisted of 6 input nodes with one output node. Optimum hidden nodes were found to be 12 and the network was trained with back-propagation algorithm. The log (1/C) values were compared with those obtained by MLRA 21 on the same set of 35 compounds. The results of the ANN were significantly better than those obtained by MLRA. A book edited by J. Devillers 22 is a good source of information for those interested in QSAR and drug design applications. Classification of the Activity of Capsaicin and Its Analogues: An ANN to model the structure-activity relationship of a large series of capsaicin analogues was reported by Hosseini23 et al. Back-propagation artificial neural networks (ANNs) were trained with parameters derived from different molecular structure representation methods, including topological indices, molecular connectivity, and novel physicochemical descriptors to model the structure-activity relationship of a large series of capsaicin analogues. In order to present the ANN with as much useful information as possible from structure, the authors investigated a variety of structural parameterization methods. These were molecular connectivity, topological indices and charged indices, connection table theory, and a simple atomic decomposition of molecules into atom type. These were used in conjunction with novel physicochemical descriptors and some simple atomic descriptors developed in this study. The design of the dataset for training and testing the ANN is a bit specialized and complex to be discussed here. Interested readers can refer to the original paper. The ANN QSAR model produced a high level of correlation between the experimental and predicted data. After optimization, the developed model correctly classified 34 of 41 inactive compounds and 58 of 60 compounds of 101 capsaicin analogues. The results demonstrated the capability of ANNs for predicting the biological activity of drugs, when trained on an optimal set of input parameters derived from a combination of Indian J.Pharm. Educ. 39(2) April - June 2005 different molecular structure representations. Antimicrobial Activity: Topological connectivity indexes were used to detect the microbiological activity in a group of heterogeneous compounds 24 . Step wise linear discriminant analysis models and ANN models were developed. Though both methods are appropriate to differentiate between active and inactive compounds, the artificial neural network was better and showed in a test set a prediction success of 98% while the linear discriminant analysis showed only 92%. QSAR of Carbonic anhydrase: Development of quantitative structure-activity relationship and classification models for a set of carbonic anhydrase inhibitors have been reported by Marttioni25 et al. Formulation Development Optimization of Formulation Parameters for Liposomes: Optimization of the formulation parameters of Cytarabine liposomes prepared by the lipid film hydration method using artificial neural networks (ANN) and multiple regression analysis has been very recently reported in an online journal by Indian investigators, Subramanian26 and coworkers. The process variables such as drying time, rotation speed, temperature, vacuum applied, and hydration time are kept constant, while the formulation variables, drug/lipid (phosphatidyl choline [PC] and cholesterol [Chol]) molar ratio (X1), PC/Chol in percentage ratio of total lipids (X2), and the volume of hydration medium (X 3), which have been predicted to play a significant role in enhancing the percentage drug entrapment (PDE) are taken as variable parameters and the PDE was selected as the dependent variable. The third independent factor, volume of hydration medium, is also a very important factor as the drug is introduced into the liposomes after dissolving in the hydration medium. As model formulations, 27 formulations were prepared. A multilayer feed-forward back-propagation network using Levenberg-Marquardt’s learning rule was used to predict PDE of the liposomal formulations. Three causal factors, drug:lipids (X1), PC:Chol (X2), and volume of hydration medium (X3) were used as each unit of input layer. The output layer was composed of one response variable PDE. The optimization methods developed by both ANN and multiple regression analysis were validated by preparing another 5 liposomal formulations. The predetermined PDE and the experimental data were compared with predicted data by paired t test, no statistically significant difference was observed. ANN showed less error compared with multiple regression analysis. Theophylline controlled release tablet: Formula optimization of theophylline controlled-release tablet based on artificial neural networks has been reported by Takayama 27 et al. 16 kinds of theophylline tablets were 65 prepared. The amounts of Controse, the mixture of hydroxypropylmethyl cellulose with lactose, cornstarch and compression pressure were selected as causal factors. The release profiles of theophylline were characterized as the sum of the fast and slow release fractions. A set of release parameters and causal factors were used as tutorial data for ANN. The optimization technique incorporating ANN showed a fairly good agreement between the observed values of release parameters and the predicted results. Optimization of Aspirin extended release tablets: Aspirin extended release tablet formulations have been optimized using ANN by Ibric 28 et al. The effects of concentration of Eudragit L 100 and compression pressure as formulation and process variables was studied on the in vitro release profile of aspirin from matrix tablets. The release profiles predicted by the generalized regression neural networks coincided well with the experimental values. Ketoprofen Hydrogel optimization: A novel simultaneous optimization technique incorporating an artificial neural network (ANN) was applied to a design of a ketoprofen hydrogel containing O-ethylmenthol by Takayama 29 e t al. For the optimization study, the amount of ethanol and O-ethylmenthol were selected as causal factors. A rate of penetration lag time and total irritation score were selected as response variables. A set of causal factors and response variables was used as tutorial data for ANN and the nonlinear relationships between the causal factors and the response variables were represented well with the response surface predicted by ANN. Salbutamol sulfate osmotic pump tablet optimization: In a study by Wu 30 et al. a formulation optimization technique using ANN has been reported. Thirty different formulations of salbutamol sulfate osmotic pump tablets were prepared, and their dissolution tests were performed. The amounts of hydroxypropyl methylcellulose (HPMC), polyethylene glycol 1500 (PEG1500) in the coating solution, and the coat weight were selected as the causal factors. Both the average drug release rate for the first 8 hr and the correlation coefficient of the accumulative amount of drug released and time were obtained as release parameters to characterize the release profiles. A part of the data of release parameters and causal factors was used as training data for the ANN, and another part of data was used as test data. The optimal formulation produced by the technique gave the satisfactory release profile since the observed results coincided well with the predicted results thus demonstrating ANNs to be quite useful in the optimization of pharmaceutical formulations. Controlled release formulation: An artificial neural network (ANN) and pharmacokinetic simulations in the design of controlled-release formulations with predictable in vitro and in vivo behavior has been reported by Chen31 66 et al. Seven formulation variables and three other tablet variables (moisture, particle size and hardness) for 22 tablet formulations of a model sympathomimetic drug were used as the ANN model input, and in vitro dissolutiontime profiles at ten different sampling times were used as output. The optimized ANN model was used for prediction of formulations based on two desired target in vitro dissolution-time profiles and two desired bioavailability profiles. For three of the four predicted formulations there was very good agreement between the ANN predicted and the observed in vitro and simulated in vivo properties. This work illustrates the potential for an artificial neural network, along with pharmacokinetic simulations, to assist in the development of complex dosage forms. Polymorphic Ranitidine determination: Ranitidine hydrochloride is antihistaminic drug that exist in two polymorphic forms known as Form 1 and Form 2. Diffuse reflectance IR spectral analysis 32 and X-Ray diffraction33 were combined with ANNs as a data modeling tool for the qualitative and quantitative control of ranitidine-HCl. The ANN was trained to recognize specific patterns of constituents of the formulations from the overall spectral pattern. When the classification ANN was exposed to complex tablet formulation samples containing only ranitidine-HCl Form 1 crystal modification, it successfully identified and quantified all components in tablet formulation down to a concentration of 0.7± 1.88%. There was no need to extract the active ingredient and Form 1 was successfully quantified in the presence of tablet excipients and additives. Tablet granulation: Prediction of a model granulation and tablet system characteristics from the knowledge of material and process variables utilizing ANNs has been reported by Kesavan34 and Peck. The formulation design contained the following variables: granulation equipment, diluent, method of binder addition, and the binder concentration. The material, process, granulation evaluation, and tablet evaluation data of the formulations were used as the data set for training and testing of the neural network models. A comparison of the neural network prediction performance with that of regression models was also done. Both the granulation model and the tablet model converged fairly rapidly in the training step. In the testing step, the predictions for all granulation model variables (geometric mean particle size, flow value, bulk density, and tap density) were satisfactory. In the tablet model, the predictions for disintegration and thickness were also satisfactory. The predictions for hardness and friability were less than satisfactory. Two situations where the neural network may not perform adequately are discussed. The neural network prediction is better or comparable to regression methods for all the predicted variables in this study. Indian J.Pharm. Educ. 39(2) April - June 2005 ANN applications for pharmaceutical formulation development have also been reported by several researchers 31, 35-38. ANN models showed better fitting and predicting abilities in the development of solid dosage forms 39, 40 in investigations of the effects of several factors (such as formulation, compression parameters) on tablet properties (such as dissolution) compared to the response surface methodology. Fluidized bed granulation processing has been modeled by Murtoniemi 41, 42 et al. The use of ANNs to examine the relative importance of formulation and processing variables in determining the dissolution profile of sustained release (SR) dosage form has been reported by Leane 43 et al. A review by Takayama 44, 45 et al. on the use of ANN as a novel method to optimize pharmaceutical formulations could be of use to formulation developers. Sun46 et al. have reviewed the basic ANN structure, the development of the ANN model and an explanation of how to use ANN to design and develop controlled release drug delivery systems are discussed. Prediction of Aerosol Deposition in Human Lungs Formulation scientists have been concerned with the problem of how best to administer medical aerosols to maximize delivery of therapeutic agents to infected regions of lung diseased patients and aerosol deposition in humans has been subjected to many years of experimental and theoretical investigation. A reliable method for predicting the pattern of aerosol particle deposition within the human lungs, using artificial neural networks was reported by Nazir47 et al. They used experimental data (regional and total deposition fractions of inhaled particles of defined sizes under well-defined breathing conditions) from the most extensive in vivo studies in human subject studies involving human volunteers published by Heyder48 et al. to train neural networks for prediction of regional and total aerosol deposition patterns in human lungs. The deposition data presented in their paper represent mean values for lung deposition fractions of mono-disperse unit density aerosols for three healthy subjects during nose and mouth breathing. In each laboratory test, the subjects were asked to inspire at a prescribed constant flow rate up to a given tidal volume, then exhaled at a similar flow rate, with no irregular pauses between inspiratory and the expiratory periods of a breath. Particle diameter, breathing cycle period, and mean inspiratory flow rate were provided to the network as input and the target output consisted of the aerosol particle regional deposition fractions. The network inputs were selected through a simple consideration of the known factors influencing the site and extent of aerosol deposition, viz., the sizes of the particles, their residence time within the airways, and the Indian J.Pharm. Educ. 39(2) April - June 2005 velocity of the air in which they are borne along within the airways49. An MLP network consisting of three input nodes, four hidden nodes, and one output node was found adequate for predicting bronchial deposition, whereas both laryngeal and alveolar deposition data necessitated the use of a 3–5–1 configuration. The three networks were trained to provide predictions for laryngeal, bronchial, and alveolar deposition fractions, respectively. The total deposition fraction for a given set of breathing conditions was computed simply as the sum of the outputs produced from the corresponding regional deposition ANNs. Secondary Structure of Protein The secondary structure of protein is of utmost importance to its biological activity and there is much interest in predicting the secondary structure of proteins from their primary structure. There are three types of secondary structures: alpha-helix, beta-sheet and random coil. In a -helix structure, the protein chain turns continuously in the same direction to form a spiral; in a b-sheet, two or more parts of the same chain are aligned parallel in space; the term coil collects all the other more or less irregular 3-dimensional arrangements of amino acids. Qian and Sejnowski are the pioneers in the use of back-propagation neural networks to predict the secondary structure of polypeptides from amino acid sequence 50. The basic assumption is that the identities of an amino acid and its neighbours determine the secondary structure of that neighbourhood. A sort of ‘window scan’ over a polypeptide segment might in principle give the secondary structure of the chain. Each amino acid is coded as a 21-bit string with one specific bit turned on and the other all zero. The 21st position of the bit vector is reserved for a special code called a spacer to handle situations when the moving window is at the beginning or end of protein chain. The input was a sequence of 13 amino acids and the output is 3 units representing the secondary structures in which the central amino acid is embedded. The training set consisted of 106 proteins, having altogether 18,105 amino acid residues and the corresponding specifications of the kind of secondary structure it is embedded in. Another 15 proteins with a total of 3,520 amino acids and their known participation in a secondary structure are taken as test set. The ANN gave 62.5% right answers on the test set, a remarkable improvement over the method of Chou5 1 and Fasman with a predictive ability of 50 %. An overview by Rost52on this is excellent. Miscellaneous HPLC optimization: The usefulness of ANNs for response surface modeling in HPLC optimization53-55 was compared with linear regression methods. Retention mapping describes the chromatographic behavior of 67 solutes by response surface, which shows the relationship between the chromatographic behavior of solutes and components of the mobile phase. The capacity factor of every solute in the sample can then be predicted, rather than performing many separations and simply choosing the best one obtained. Experiments confirmed that predicted capacity factors of solutes obtained by ANNs were better than those obtained with multilinear stepwise regression model. Electrophoretic mobility: It is the most important parameter governing the separation of solutes in capillary zone electrophoresis. Qianfeng56 et al. built a new model by means of a multilayer neural network using extended delta-bar-delta algorithm to estimate complex property of electrophoretic mobilities of aliphatic carboxylates and amines from simpler experimental properties. The molecular weight (W), molecular volume (V), the code (+1 or -1) of acid and base and pK value were used as input parameters to predict electrophoretic mobility. The optimum artificial neural networks model was found to be internally valid and could give excellent prediction results yielding accurate predictions for a large external set. Bacterial fingerprinting: Three rapid spectroscopic approaches for whole-organism fingerprinting – pyrolysis mass spectrometry (PyMS), Fourier transform infra-red spectroscopy (FT-IR) and dispersive Raman microscopy – were used to analyse a group of 59 clinical bacterial isolates associated with urinary tract infection by Goodacre 57 et al. The artificial neural network (ANN) approaches exploiting multi-layer perceptrons or radial basis functions could be trained with representative spectra of the five bacterial groups so that isolates from clinical bacteriuria in an independent unseen test set could be correctly identified. Comparable ANNs trained with Raman spectra correctly identified some 80% of the same test set. Physicochemical properties of organic compounds: The literature describing neural network modeling to predict physicochemical properties of organic compounds from the molecular structure is reviewed from the perspective of pharmaceutical research by Taskinen58 et al. The standard three-layer, feed-forward neural network is the technique most frequently used, although the use of other techniques is increasing. Various approaches to describe the molecular structure have been successfully used, including molecular fragments, topological indices, and descriptors calculated by semi-empirical quantum chemical methods. Some physicochemical properties, such as octanol-water partition coefficient, water solubility, boiling point and vapour pressure, have been modeled by several research groups over the years using different approaches and structurally diverse large training sets. The prediction accuracy of most models seems to be 68 rather close to the performance of the experimental measurements, when the accuracy is assessed with a test set from the working database. Results with independent test sets have been less satisfactory. Implications of this problem are discussed. Clinical Medicine: Recently prediction of HIV drug resistance with neural networks has been reported by Drachici 59 et al. They demonstrated that the drug resistance can be predicted from either the structural features or protein sequence of the HIV protease. Novel artificial neural network for early detection of prostate cancer has been reported by Djavan 60 et al. An evolutionary artificial neural networks approach for breast cancer diagnosis has been reported by Abbass61 and his team. A neural computational aid to the diagnosis of acute myocardial infarction has been studied by Baxt 62 et al. A review by Khan63 et al. on ANN and medicine may be of interest to those involved in clinical pharmacy. The above survey is by no means exhaustive but should be sufficient to indicate the implications of ANNs in pharmacy. It is hoped that it would serve as motivational factor to lead the interested reader into contemplating some applications in his area of interest in pharmaceutical sciences. The next and final part (part-4) of the tutorial review would cover the grey areas untouched till now such as data processing, performance evaluation, some relevant mathematics, ANN software and resources on neural networks in print and Internet. References 1. Fausett, L., In; Fundamentals of Neural Networks: Architectures, Algorithms and Applications, New Jersey: Prentice-Hall Inc, 1994, 1. 2. Despagne, F and Massart, D.L., Analyst, 123, 1998, 157R-178R. 3. Balamurugan, C…. et al., Indian J. Pharm. Sci., 65, 2003, 274-278. Sathyanarayana, D., Kannan K. and Manavalan R., Indian J.Pharm. Sci., 66, 2004, 245 - 751. 4. 4a. Sathyanarayana D., Kannan K. and Manavalan R., Principal component artificial neural network calibration models for simultaneous spectrophotometric estimation of Phenobarbitone and Phenytoin sodium in tablets, Acta. Chim. Slov., 2005, Accepted for publication. 4b. Sathyanarayana D., Kannan K. and Manavalan R., Development of an Artificial Neural Network Tool for Multi-component Pharmaceutical Dosage Analysis, Annamalai University J. Engg. Tech., Accepted for publicaion. 5. Yin, C., Shen, Y., Liu, S., Yin, Q., Guo, W. and Pan, Z., Computers and Chemistry, 25, 2001, 239-243. Indian J.Pharm. Educ. 39(2) April - June 2005 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. Ni, Y., Liu, C. and Kokot, S., Analytica Chimica Acta, 419, 2000, 185–196. Chen, Y… et al., Drug Dev Ind Pharm., 27, 2001, 623-31. Duponchel, L., Ruckebusch, C., Huvenne, J.P. and Legrand, P., J. Near Infrared Spectrosc. 7, 1999, 155166. Chow, H., Tolle, K.M., Roe, D.J., Elsberry, V. and Chen, H., J. Pharm. Sci., 86, 1997, 840-845. Rumelhart, D. E., Hinton, G. E. and Williams, R. J., In Parallel Distributed Processing; Rumelhart, D. E. and McClelland, J. L., Eds.; Cambridge;MIT Press, 1986, 45-76. Rumelhart, D. E., Widrow, B. and Lehr, M. A., Commun. ACM, 37, 1994, 87-92. Nishizawa, K… et al., J. Pharm. Pharmaceut. Sci, (www.ualberta.ca/~csps) 1(3), 1998, 95-101. Rumelhart, D.E., Hinton G.E. and Williams, R.J., Nature, 323, 1986, 533-536. Yamamura, S., Advanced Drug Delivery Reviews, 55, 2003, 1233-1251. Smith, B.P. and Brier, M.E., J. Pharm. Sci., 85, 1996, 65-69. Gobburu, J.V.S. and Chen, E.P., J. Pharm. Sci., 85, 2002, 505-510. Gobburu, J.V.S. and Shelver, W.S., J. Pharm. Sci., 84, 1995, 862-865. Wessel, M.D… et al., J. Chem. Inf. Comput. Sci., 38, 1998, 726-735. Aoyama, T., Suzuki, Y. and Ichikawa, H., J. Med. Chem., 33, 1990, 905-908. Aoyama, T., Suzuki, Y. and Ichikawa, H., J. Med. Chem., 33, 1990, 2583-2590. Yoshimoto, M… et al., J. Med. Chem., 22, 1979, 491496. J. Devillers (Ed.), Neural Networks in QSAR and Drug Design, London: Academic Press, 1996. Hosseini, M., Maddalena, D. J. and Spence, I., J. Chem. Inf. Comput. Sci., 37, 1997, 1129-1137. Garcoa-Domenech, R. and Julian-Ortiz, J.V., J. Chem. Inf. Comput. Sci., 38, 1998, 445-449. Mattioni, B.E. and Jurs, P.C., J. Chem. Inf. Comput. Sci., 42, 2002, 94-102. Subramanian, N., Yajnik, A., Murthy, R.S.R., AAPS Pharm. SciTech. 5(1), 2004, article 4. (www.aapspharmscitech.org) Takayama, K… et al., Journal of Controlled Release, 68, 2000, 175-186. Ibric, S…. et al., AAPS Pharm. Sci. Tech., 4(1), 2003, Article: 9 (http://www. aapspharmscitech.org) Indian J.Pharm. Educ. 39(2) April - June 2005 29. Takayama, K., Takahara, J., Fujikawa, M. and Nagai, T., Journal of Controlled Release, 62,1999, 161-170. 30. Wu, T., Pan, W., Chen, J. and Zhang, R., Drug Dev. Ind. Pharm., 26, 2000, 211-215. 31. Chen, Y., McCall, T.W., Baichwal, A.R. and Meyer, M.C., J. Control. Release, 59, 1999, 33-41. 32. Agatonovic-Kustrin, S., Tucker, I.G. and Schmierer, D., Pharm. Res., 16, 1999, 1479-1484. 33. Agatonovic-Kustrin, S., Wu, V., Rades, T., Saville, D. and Tucker, I.G., Int. J. Pharm. 184, 1999, 107114. 34. Kesavan , J.G., and Peck, G.E., Pharm Dev Technol., 1, 1996, 391-404. 35. Bourquin, J., Schmidli, H., Van Hoogevest, P. and Leuenberger, H., Pharm. Dev. Technol., 2, 1997, 95109 and 111-121. 36. Hussain, A.S., Yu, X. and Johnson, R.D., Pharm. Res., 8, 1991, 1248-1252. 37. Hussain, A.S., Sivanand, P., Johnson, R.D., Drug Dev. Ind. Pharm., 20, 1994, 1739-1752. 38. Ebube, N.K., McCall, T., Chen. Y. and Meyer, M., Pharm. Dev. Technol., 2, 1997, 225-232. 39 Takahara, J., Takayama, K. and Nagai, T., J. Control. Release, 49, 1997, 11-20. 40. Bourquin, J., Schmidli, H., Van Hoogevest, P. and Leuenberger, H., Eur. J. Pharm. Sci., 7, 1998, 1-12. 41. Murtoniemi, E… et al., Int. J. Pharm. 110, 1994, 101108. 42. Murtoniemi, E…. et al., Int. J. Pharm., 108, 1994, 155164. 43. Lean, M.M., Cumming, I. and Corrigan, O.I., AAPS Pharm. Sci. Tech., 4, 2003, Article-26 (http:// www.aapspharmscitech.org). 44. Takayama, K., Fujikawa, M. and Nagai, T., Pharm. Res., 16, 1999, 1-6. 45. Takayama, K., Fujikawa, M., Obata, Y., and Morishita, M., Adv. Drug Delivery Reviews, 55, 2003, 1217-1231 46. Sun, Y., Peng, Y., Chen, Y. and Shukla, A.J., Advanced Drug Delivery Reviews, 55, 2003,12011215. 47. Nazir, J… et al., Pharm. Res., 19, 2002, 1130-1136. 48. Heyder, J…. et al., J. Aerosol Sci. 17, 1986, 811–825. 49. Stahlhofen, W., Rudolf, G. and James., A.C., J. Aerosol Med., 2, 1989, 285–308. 50. Qian, N. and Sejnowski, T.J., J. Mol. Biol., 202, 1988, 865-884. 51. Chou, P.Y. and Fasman, G.D., Biochemistry, 13, 1974, 211-222. 69 52. Rost, B., in Encyclopedia of Computational Chemistry, Eds. : Schleyer, P.V.R…. et al., Chichester:Wiley, 1998, 2242-2255. 53. Metting, H.J. and Coenegracht, P.M., J. Chromatogr., A728, 1996, 47-53. 54. Agatonovic-Kustrin, S., Zecevic, M., Zivanovic, L.J. and Tucker, I.G., Anal. Chim. Acta, 364, 1998, 265273. 55. Agatonovic-Kustrin, S., Zecevic, M., Zivanovic, L.J. and Tucker, I.G., J. Pharm. Biomed. Anal., 17, 1998, 69-76. 56. Li, Q., Dong, L., Jia, R., Chen, X., Hu, Z. and Fan, B.T., Computers and Chemistry, 26, 2002, 245–251. 70 57. Goodacre, R.E…. et al., Microbiology, 144, 1998, 1157–1170. 58. Taskinen, J. and Yliruusi, J., Advanced Drug Delivery Reviews, 55, 2003, 1163-1183. 59. Draghici, S. and Potter, R.B., Bioinformatics, 19, 2003, 98–107 60. Djavan, B…. et al., J Clin Oncol., 20, 2002, 921-929. 61. Abbass, H.A., Artif. Intell. Med., 25, 2002, 265-281. 62. Baxt, W.G., Shofer, F.S., Sites, F.D. and Hollander, J.E., Ann. Emerg. Med., 39, 2002, 366-373. 63. Khan, Z.H….. et al., Indian J. Physiol. Pharmacol., 42, 1998, 321-42. Indian J.Pharm. Educ. 39(2) April - June 2005 Pharmacognosy Review Article Emerging Challenge of Herb-Drug Interaction U. N. Harle and N. J. Gaikwad Department of Pharmaceutical Sciences, University Campus, Nagpur 440 033 Received on 2.11.2004 Accepted on 13.1.2005 ABSTRACT The use of herbal products is rising leading to co administration of herbals with medicinal drugs and the likelihood of a clinically relevant interaction is raising high. The objective of this review is to explore such interaction and tabulate new methodology useful to predict new interactions. A number of potent pharmacological interactions have been recognized between phytochemicals and medicinal drugs and some are the case reports in clinical practise. Herbal medicines and vegetables, which modulate physiological parameters like cytochrome P450s enzyme system, efflux transporters PgP or modulation of Ah receptors are selected to categorise them in various chemical class. Among the wide range of phytochemicals, piperine has been identified in clinical trials that increases plasma concentration of phenytoin, propranolol, and theophylline by inhibiting CYP3A4 activity and modulating gastric emptying time. Furthermore, bergamottin, hypericin and hyperforine were investigated for having the ability to increase bioavailability of many medicinal drugs by modulating CYP3A4 activity. Some herbal alkaloids (vincristine, rutaecarpine, evodamine and dehydroevodiamine), class of AQ, triterpenoids, and flavonoids serve as substrates, inducers or inhibitors of CYP’s. Herbs are classified according to the chemical class and their physiological targets results in interaction emergencies. The current misconception about safety of herbs is becoming invalid as the phytochemicals are able to modulate various physiological factors and interact with medicinal drugs and therefore these interactions should be rigorously tested. INTRODUCTION Exposure of the human body to exogenous chemicals is a continuous, inevitable and unavoidable process. Among the vast majority of chemicals to which man is exposed are nature based chemicals of plant origin. It has been estimated that more than 99% of the chemicals ingested by humans are naturally occurring 1. Herbal remedies are administered on chronic basis, which dramatically increase the intake of phytochemicals that would otherwise be consumed at low levels. The first report of herb-drug interaction published in 1970s, stated that consumption of cruciferous vegetables resulted in lower plasma levels of analgesic drug phenacetin 2. It was suggested that indoles, which are present in such vegetables enormously, could be responsible for interaction2. In this report, many herb-drug interactions have been reported and reviewed. But it has been discerned that many medicinal herbs and pharmaceutical drugs are therapeutic at one dose and toxic at another. Therefore, interactions between herbs and drugs may increase or decrease the pharmacological or toxicological effects of either component. Reviews published previously in the same context suggested, herb-drug interaction as a theoretical possibility and of lesser importance has given room to the clinical relevance and significance of phytochemicals responsible for herb-drug interaction. Many of the reviewers have stated that ‘herbal medicines are ubiquitous: the dearth of reports of adverse events and interactions probably reflect a combination of under-reporting and the benign nature of most herbs used’3 . The true prevalence of drug interactions is substantial but unknown 4. But till date there are various clinical relevant herb-drug interactions reported that call Indian J.Pharm. Educ. 39(2) April - June 2005 our attention towards the possibility of clinical compliance from herb-drug interaction. The case report has stated that herbs traditionally used to decrease glucose concentrations in diabetes have precipitated hypoglycaemia when taken in combination with conventional medicinal hypoglycaemic agents 5. The clinical relevance of phytochemicals is not focused by many review published on herb drug interactions. An attempt has been made through this review to admit the relevance of phytochemicals, responsible for interaction. Phytochemicals apart from medicinal herbs, cruciferous vegetables containing phenethyl isothiocyanate and sulforephane are also capable of modulating cytochrome P 450 and interfere with metabolism of medicinal drugs5. However, the picture is more complex as cruciferous vegetables also influence enzyme systems other than CYP family, so the effects of these vegetables on metabolism of a certain drug will be very much dependent on the nature of the active phytochemicals present in such vegetables 3. For example, cruceferious vegetables containing indoles also modulate the activity of enzymes other than CYP family, upregulating conjugation reactions such as glutathione, Stransferases and glucuronyl transferases 2, and downregulating the flavin monooxygenase system6. In clinical practice, polypharmacy is common, and thus, all ingested phytochemicals in the form of herbs as food, are potent to interact with each other. Most of the possible herb-drug interactions may be classified in two major categories viz pharmacokinetic and pharmacodynamic interactions. 71 Pharmacokinetic Interactions Despite of the limitations of the in vitro/in vivo studies, as well as animal vs. human studies, there are many studies reported for the pharmacokinetic herb-drug interactions. Factors, which can modulate the pharmacokinetic of the herb or drugs, are discussed as follows. Absorption The physical passage of herbs or drugs from the outside to the inside of the body occurs by means of intestine. The majority of all absorptions occur in the intestine, where herbs or drugs must pass through the intestinal wall to enter the blood. Several mechanisms may interfere with the absorption of drugs through the intestine. The influence of herbs on the absorption of drugs is well narrated by many of the reviewers but there are also reports of change in absorption of herbs by co administration of the drugs. For example, drugs such as cholestyramine, colestipol and sucralfate bind to certain herbs, forming an insoluble complex, and decrease absorption of both substances because the size of the insoluble complex is too big to pass through the intestinal wall. There are reports of herb-herb interaction precipitated by those drugs, which change the pH of the stomach. With the subsequent decrease of stomach acid, herbs may not be broken down properly, leading to poor absorption in the intestine. Drugs, which change the pH of stomach by affecting the secretion of stomach acid, are antacids, cimetidine, famotidine, nizatidine, ranitidine and omeprazole 7 . Furthermore, herbs, which affect gastrointestinal motility, may even alter the absorption of drug. Slower gastrointestinal motility means the drug stay in the intestine for a longer period of time and there will be an increase in absorption. Conversely, faster gastrointestinal motility means the drugs stay in the intestine for a shorter period of time and there may be a decrease in absorption. Agar is well known laxative drug that causes dehydration in moderate doses. Drugs such as metoclopramide and cisapride increase gastrointestinal motility which may possibly decrease absorption of herbs; and drugs such as haloperidol decrease gastrointestinal motility and may increase absorption of herbs. Therefore, it may be necessary to alter the dosage of herbs when the patient takes a drug that affect the gastrointestinal motility and change overall absorption. Any herbal laxative or bulk-forming agents will speed intestinal transit, and thus may interfere with the absorption of almost any intestinally absorbed drug. The most popular laxative herbs are anthranoid-containing herbs such as senna (Cassia senna and C angustifolia) and cascara sagrada (Rhamnus purshiana). Dried exudate from the aloe vera (Aloe barbadensis) leaf (not gel) also contains anthranoids and is used as a laxative. Aloe vera gel, found within the leaves, is used topically for burns and cuts, and is sometimes recommended to treat ulcers and other disorders. The gel (or juice made from the gel) does not contain anthranoids, but the laxative leaf may contaminate some oral preparations. Less commonly used anthranoid-containing plants are frangula (R hamnus frangula), yellow dock (Rumex crispus), and Chinese rhubarb (Rheum officinale). Various herb-drug interaction and major phytochemicals are capsulised in table-1. Table-1: Herb-drug interaction and the resultant complications 72 Herbs Aconite (Aconitum napellus) Agar (Gelidium cartilagineum) Agrinomy (Agrimonia eupatoria) Aloe (Aloe vera) Angelica (Angelica dahurica) Phytochemicals Aconitine; Hypoaconitine Agarose; Agaropectine Interaction and comments Antihypertensives and cardiac glycosides: Increased toxicity and death may occur68. Electrolyte solution and tannic acid: Dehydration69. Ellagitannins Anticoagulants: Decrease in clotting time70 . Berbaloin; Aloeemodine; aloin Xanthotoxin; Osthol; Bergapten Cardiac glycosides and antiarrhythmic agents: Potentiating effect on heart by reducing potassium via laxative effect71. Tolbutamide: P Pronoged rolongedhalf-life and reduced the clearance72. Astragalus (Astragalus membranaceus) Basil (Ocimum sanctum) Astragalan; Bassorin; Astramembranin Cyclosporine, azathioprine, methotrexate: Impair immunosuppressive activity71, 73. Linolol; Estragole Insulin: Potentiation of hypoglycaemic effect21 . Indian J.Pharm. Educ. 39(2) April - June 2005 Betel nut (Areca catechu) Arecoline Bilbery (Vacinium myrtillus) Black haw (Viburnum prunifolium) Broom (Sarothamnus scoparius) Buckthorn (Rhamnus cathartica) Burdock (Arctium lappa) Capsicum pepper (Capsicum frutescens) Cascara Sagrada (Rhamnus purshiana) Catnip (Nepeta cataria) Chamomile (Matricaria chamomilla) Devil's claw (Harpagophytum procumbens) Dong quai (Angelica sinensis) Eleuthero (Eleutherococcus senticocus) Ephedra (Ephedra sinica) Cinnamic acid; Benzoic acid Scoplin; Scopoletin Garlic (Allium sativum) Organosulfur compounds- Thioester allyl sulphide, allicin, diallyl suphide, diallyl disulphide Ginkgolides Ginkgo (Ginkgo biloba) Ginseng (Panax ginseng) Flupenthixol and procyclidine: Rigidity, bradykinesia, jaw tremor 74. Fluphenazine: Tremor, stiffness, akithesia74. Prednisone and salbutamol: Inadequate control of asthma75. Anticoagulants, antiplatelete agents: Potentiation of the effect76. Anticoagulats: Increase in the anticoagulant effect77. Spartteine; Scoparoside Increased the effect of antiarrhythmics, antihypertensives and cardiac glycosides78. Emodin Anthraquinones Antiarrhythmics, cardia glycosides, corticosteriods and Thiazide diuretics: Hypokalemia 79 . Antidiabetics: Hypoglycemia80 . Capsaicin Antiarrhythmic and cardiac glycosides: Hypokalemia81. Cascarosides; Barbaloin Antiarrhythmic and cardiac glycosides: Hypokalemia82. Nepetalactone; Thymol Sedatives: Sedation potentiation83. Chamaemeloside; Chamazulene Sedatives: Sedation Potentiation84 . Kempferol; Luteolin; Harpagoside Warfarin: Increased and prolonged action85. Osthole ; Psoralen ; Safrole Ginsenosides Warfarin: Increased and prolonged action86, 87. Ephedrine MAO inhibitors: Concurrent use causes hypertension. Cardiac glycosides or halothane: Cardiac arrhythmia Caffeine intensifies cardiovascular side effects 89. Warfarin: Postoperative bleeding90, 91, spontaneous spinal epidural haematoma92. Diallyl suphide, diallyl disulphide suppresses hepatic CYP2E193. Ginsenosides and two eleutherosides Digoxin: Raised digoxin concentrations88 . Aspirin: Spontaneous hyphema94-96. Paracetamol and ergotamine/caffeine: Bilateral subdural haematoma97, Subarachnoid haemorrhage98. Warfarin: Intracerebral haemorrhage99. Thiazide diuretic: Hypertension 100. Warfarin: Decreased INR101 . Phenelzine: Headache and tremor102, mania 103. Alcohol: In mice, ginseng increases the activity of alcohol dehydrogenase and aldehyde dehydrogenase104. Ginseng is reported to inhibit cDNA expression of CYP450 enzymes119 . 51 Indian J.Pharm. Educ. 39(2) April - June 2005 73 Grapefruit juice Bergamottin Karela or bitter melon (Momordica charantia) Liquorice (Glycyrrhiza glabra) Momordicine Papaya (Carica papaya) Psyllium (Plantago ovata) Rhubarb (Rheum palmatum) Shankhapushpi (Ayurvedic mixed-herb syrup) Papin St John's wort (Hypericum perforatum) Glycyrrhetinic acid; Glycyrrhizin; Glycyrrhizin acid. Verbascoside; Homoplantaginin Rhein; Senosides; Gallic acid Aqueous extract of Evolvulus alsinoides Linn, Convolvulus Pluricaulis Choisy Hypericin; hyperforin Diazepam: Increased plasma level and activity51. Vinblastine: Decrease plasma level15 . Chlorpropamide: Glycosuria106. Prednisolone: Increases concentration in the plasma107. Hydrocortisone: Glycyrrhetinic acid potentiates of cutaneous vasoconstrictor response121. Oral contraceptives: Hypertension, oedema and hypokalaemia109. Glycyrrhizin increase the activity of CYP2B, CYP1A 122. Warfarin: Increased INR 85. Lithium: Decreased lithium activity102 . Cardiac glycosides and antiarrhythmic agents: Hypokalemia71-73. Phenytoin: loss of seizure control117. Paroxetine: Lethargy/incoherence118. Sertraline: Mild serotonin syndrome105. Nefazodone: Mild serotonin syndrome105. Theophylline: Decreased activity120. Phenprocoumon: Modulate activity108. Oral contraceptive (ethinyloestradiol): Breakthrough bleeding109. Cyclosporin: Decrease plasma levels by stimulating CYP3A4 activity and increased expression of Intestinal Pgp 14, 110. Protease inhibitors: Decrease plasma concentration of indinavir111. Oral contraceptives: Increased deactivation of steroid through CYP3A-mediated metabolism66. Alprazolam: Plasma level lowered112. Anticoagulants: Decreased plasma level and loss activity of warfarin113 . Amitriptyline: Decrease the AUC114. Aspirin: Increased bioavailability 115. Tamarind (Tamarindus Tartaric acid; Potassium indica) barbarate Valerian (Valeriana Valeric acid; Terpinols Alcohol: Reduces the adverse effect of alcohol116. officinalis ) Yohimbe Yohimbine Tricyclic antidepressants: Hypertension117. (Pausinystalia yohimbe) Note: INR=International Normalized Ratio; AUC=Area Under the Concentration/time curve. Effect of phytochemicals on P-glycoprotein Efflux transporters proteins present in the intestine also affect absorption of drug. P-glycoprotein (Pgp) is a plasma membrane-bound drug efflux protein found primarily in drug-eliminating organs and presumably functions as a detoxifying transporter because it actively extrudes xenobiotics from the body8. In the small intestine, P-gp has been localized to the apical membrane of the 74 intestinal epithelial cells, having a role of effluxing the compounds back into the intestinal lumen. Pharmacokinetic studies of paclitaxel, digoxin, and CsA in mdr1a knockout mice have revealed the importance of intestinal P-gp in limiting the oral bioavailability of these drugs 9. Phytochemicals are also known to interact with the ATP-dependent transporter proteins such as the intestinal P-glycoprotein and other multidrug resistance Indian J.Pharm. Educ. 39(2) April - June 2005 proteins that facilitate the efflux of the drugs11-13. St. John’s wort administration was reported to decrease the blood/plasma concentrations of cyclosporine, indinavir and digoxin. The mechanism of interaction is the direct effect of St. John’s on intestinal P-glycoprotein/MDR1 (in human and rats), hepatic CYP3A2 (in rats), and intestinal and hepatic CYP2A4 (in humans) 14. Inhibition of vinblastine efflux is also reported to be mediated by Pglycoprotein by grapefruit juice components in coca-2 cells 15. Therefore, to minimize the risk of interaction, it is best if the drugs and the herbs are taken separately by approximately two hours. Distribution At present, herb-drugs interaction is not reported by affecting distribution. Interactions occur during the distribution phase if the drugs are highly protein-bound. For example, warfarin is an anticoagulant highly bound to protein and has a very narrow range of safety index. Warfarin interacts with various drugs, vitamins and food materials. Some known examples that interact with warfarin include aspirin, ibuprofen, vitamin K, some types of tea, green leaf vegetables and the like. These items interact with warfarin by either enhancing its effectiveness and thus leading to prolonged bleeding, or by decreasing its effectiveness and thus increasing the risk of blood clots in the vessels, both of which may be very dangerous to the patients. Agrimonia eupatoria has been reported to interfere with the efficacy of anticoagulants 5. Therefore patients who are taking warfarin need to be exceedingly cautious when taking herbs concurrently. Unfortunately, it is extremely difficult to predict whether an individual herb will interact with warfarin, because there are very few tests or experiments documented for prediction of such interactions. The best precautionary measure is close observation of the patient’s condition. If the patient shows abnormal signs of bleeding and bruises, then the dosage of herbs may need to be adjusted and the patient’s medical doctor should be contacted immediately. Metabolism The body cannot discriminate a natural chemical emanating from the garden and a synthetic chemical generated in a laboratory, and consequently it reacts to both in the same way. As the chemicals cannot exploit beneficially by the body, they are recognized as being foreign (xenobiotics), and potentially deleterious, so the immediate response of the body is to eliminate them. A large number of phytochemicals that gain access to the systemic circulation tend to be lipophilic, and consequently difficult to excrete; the body renders these hydrophilic through metabolism to facilitate their excretion16. The most versatile enzyme system involved in metabolism of phytochemicals and medicinal drugs is Indian J.Pharm. Educ. 39(2) April - June 2005 the cytochrome P45017. Since the same enzyme system is responsible for the metabolism of naturally occurring chemicals and medicinal drugs, the herb-drug interactions need not surprise us. Phytochemicals at the dietary levels can modulate the hepatic and extra hepatic expression of cytochrome P450 levels resulting in marked changes in the metabolism of drugs that lead to adverse drug interactions18. Effect of phytochemicals on cytochrome P450 Cytochrome P450 (CYP) is the most important Phase I drug-metabolizing enzyme system, responsible for the metabolism of various xenobiotics including therapeutic drug and phytochemicals 19,20. The relative abundance of the hepatic CYPs in humans has been determined as CYP1A2 (13%), 2A6 (4%), 2B6(<1%), 2C (20%), 2D6 (2%), 2E1 (7%), and 3A4(30%)21, 22. The significance of the individual CYP enzyme in human drug metabolism varies, with CYP3A, CYP2D, and CYP2C being responsible for the metabolism of 50, 25, and 20%, respectively, of the currently known drugs 21, 23. Drug interactions can frequently arise when drugs are co administered and one drug modulates the metabolic clearance of the second drug by inhibition or induction of a specific CYP enzyme, possibly leading to some fatal interactions24, 25. Many phytochemicals have been found to modulate the expression and catalytic activity of various CYP isoforms. For example, broccoli up-regulated a number of cytochrome P450 enzymes in the liver and colon of the rats 26. It was eventually established that indol-3-carbinol, which is present in the form of glucosinolate and glucobrassicin, are released by the action of the enzyme myrosinase in the stomach affects the cytochrome P450 system 27-29 . Cruciferous vegetables containing isothiocynate compounds, such as phenethyl isothiocynate and sulforaphane also modulate cytochrome P450 activity1, 5, 30, 31. Phytochemicals in tea, at dietary levels of intake, are capable of altering the hepatic cytochrome P450 profile 32. Grapefruit constituents, furanocoumarins, in general, are known to inactivate cytochrome P450 through mechanism-based process33-35. Other constituent, bergamottin has also proved to reduce CYP4A activity more effectively than its dihydroxylated metabolite35. A. Piperine Piperine is a pungent alkaloid present in Piper nigrum Linn, was reported to have antidiarrhoeal 36 , antiinflammatory 37, immune-enhancing, anticonvulsant and antioxidant activity38. Piperine inhibited gastric emptying of solids/liquids in rats and gastrointestinal transits in mice in a dose- and time-dependent manner36. Piperine inhibited CYP3A4 activity in humans39. Piperine may work as a drug bioavailability enhancer, which is evident by 75 the increase in the Cm a x and AUC of phenytoin, propranolol, and theophylline by co administration of piperine40, 41. B. Flavonoids Flavonoids are a diverse group of phytochemicals that are produced by various plants including medicinal herbs (e.g., Silybum marianum, Alpinia officinarum, Hypericum perforatum) 42 . Flavonoids are structurally classified into eight groups: flavins, flavvanones, isoflavanones, flavones, isoflavones, anthocyanides, chalcones, and flavonolignans. Flavonoids exhibit antibacterial, anti-viral, anti-inflammatory, anti-angiogenic, analgesic, hepatoprotective, cytostatic, apoptotic, estrogenic activity and possess ability to modulate several enzymes and cell receptors 38. Many flavonoids have been reported as potent inducers of various CYPs 43-45. The mechanism for the induction of CYPs by flavonoids may involve direct stimulation of gene expression via a specific receptor and/or CYP protein or mRNA stabilization 25, 46 . Flavonoids like 2,3,7,8tetrachlorodibenzo-p-dioxin (TCDD), induce CYPs via binding to aryl hydrocarbon (Ah) receptor, a ligand activated transcription factor47. For example quercetin, one of the most abundant naturally occurring flavonoid, bind as an antagonist to Ach receptor48. Flavonoids present in grapefruit juice significantly increased the oral bioavailability of most dihydropyridines (e.g., felodipine), terfenadine, saquinavir, cyclosporine, midazolam, triazolam, and verapamil 49, 50 . Bergamottin, a furanocoumarin isolated from grapefruit juice, has been reported to increase diazepam bioavailability51. C. Triterpenoids Triterpenoids exist in many herbal medicines, exhibits anticancer, anti-allergic, immunomodulatory, antihypertensive, hepatoprotective, antiviral, hypoglycemic, antifungal and molluscicidal activities 52, 53. a-Hederin (a triterpenoid saponin) significantly decreased the total hepatic CYP content, and the activity of microsomal methoxyresorufin O-demethylase (CYP1A), ethoxyresorufin O-deethylase (CYP2B), and alanin hydroxylase (CYP2E1) in the mouse54. Oleanolic acid, a triterpenoid, dose dependently reduce total liver microsomal CYP and cytochrome b content55. Further, there is insufficient data of triterpenoid-drug interaction therefore further studies are required to assess the influence of triterpenoids on drug metabolism. D. Anthraquinones Anthraquinones (AQ) exists in variety of herbs, known to interact with CYPs in three ways: 1) as a substrate of CYPs; 2) as an inducer of CYPs; and 3) as inhibitor of CYP. For example, emodine, present in laxative herbs, is metabolized to 2-hydroxyemodin mainly by 76 CYP1A256. Emodine treatment induces CYP1A1 and CYP1B1 mRNA in human lung carcinoma and breast cancer MVF-7 cells 38. But AQ administration has shown no significant effect on intestinal drug metabolizing enzymes 38. E. Polyphenols Polyphenols are family of compounds occurring in black and green teas, variety of medicinal herbs, fruits and vegetables. In vitro animal studies have indicated that polyphenols have chemoprotective, antifatigue, neuroprotective, antioxidant, anticancer, and hypolipidemic activities 57-59. Polyphenols may modulate CYPs in two ways: 1) modulating the expression; and 2) modulating the activity. For example, catechin are the major polyphenol, increased the expression of CYP1A2 in rats 60. Gallic acid, a polyphenol found in wine and herbal tea, inhibits CYP3A activity in human liver microsomes 61. Ellagic acid is a naturally occurring plant polyphenol found to decrease the hepatic CYP content, cytochrome reductase activity and CYP2E1-catalyzed pnitrophenol hydroxylation62. F. Alkaloids Alkaloids exist in number of herbal medicines and serves as a substrate, inducer or inhibitor of various CYPs. For example, some coumarine-type of alkaloids are substrates of CYP2A663. However, cephaeline and emetine are potent inhibitors of CYP2D6 and CYP3A464. Some alkaloids (e.g., rutarcarpine, evodiamine, and dehydroevodiamine) isolated from evodia rutaecarpa inhibited 7-methoxyresorufin O-demethylase and 7ethoxyresorufin O-deethylase (both are CYP1A) activities in mouse liver microsomes and interfere with the metabolism of tolbutamide, chlorzoxazone and nifedipine65. Elimination In addition to the liver, the kidney is also responsible for eliminating herbs and drugs from the body. Herbs and drugs acting on the Pgp present in the tubular membrane can affect the elimination of either or both. Further, some herbs are known diuretic agents can affect the excretion of medicinal drugs. The nephrotoxic drug induces kidney damage results in slow rate of elimination leading to an accumulation of herbs and drugs in the body. Important examples of drugs that damage the kidneys include amphotericin B, methotrexate, tobramicin and gentimicin. Therefore, as a prophylactic measure, it may be necessary to lower the dose of herbs to avoid unnecessary and unwanted side effects. Pharmacodynamic Interactions Pharmacodynamic interactions are generally more difficult to predict and prevent than pharmacokinetic interactions. Most of the pharmacodynamic interactions Indian J.Pharm. Educ. 39(2) April - June 2005 known are documented through actual cases as opposed to laboratory experiment results. The best way to prevent pharmacodynamic interactions is to watch the patient closely and monitor all clinical responses including signs, symptoms and any abnormal reactions. Examples of pharmacodynamic interaction include additive and antagonistic interactions. Betel nut (Areca catechu) interact with Flupenthixol and procyclidine, Fluphenazine and results in Rigidity, bradykinesia, jaw tremor74. Nepeta cataria potentiates sedation by oral sedative agents 83. CONCLUSION Co administration of herbals with medicinal drugs is frequent and the likelihood of a clinical relevant interaction is high. Despite of the data shown by most of the literature it is likely that such interactions are common than generally thought, but are under-reported and appearance of adverse effects may be attributed to the disease for which the treatment is taken. Therefore, interaction between herbal remedies and medicinal drugs are not any more just a theoretical possibility. The interaction between cyclosporine and St John’s wort is now well-documented66 and the underlying mechanisms are reasonably well understood, but further interactions can only be avoided if this under-researched crucial area of pharmacology receives proper attention. A number of other potent pharmacological interactions have been recognized in this decade and cytochrome P450s enzyme system, efflux transporters Pgp and Ah receptors are found to be major targets for herb-drug interaction. There are many sources of phytochemicals, including herbal medicines, vegetables and food materials and it is not feasible to check the intake. Therefore knowingly or unknowingly these agents act on the physiological targets resulting in herb-drug interaction and any untoward effect is considered as adverse effect of drug. These phytochemicals interacting with medicinal drugs are identified. Piperine has been shown in clinical trials to increase plasma concentration of phenytoin, propranolol, and theophylline40, 41. The mechanism of interaction may be by inhibiting CYP2A4 activity and decreasing gastric emptying time of drugs36, 39. Flavonoid present in grapefruit juice inhibits the activity of CYP and PgP49. Bergamottin, a furanocoumarine from grapefruit juice, was investigated for its ability to increase bioavailability by modulating CYP activity 51 . Two components of St John’s wort, hypericin and hyperforine are believed to increase CYP3A4mRNA levels 67. Clinical studies have documented that St John’s wort reduces the plasma concentration of cyclosporine, amitriptyline, digoxine, indivarin, nevirapine, oral contraceptives, warfarin, phenprocoumarin, theophylline, simivastin, and nortriptylline. Some herbal alkaloids (vincristine, rutaecarpine, evodamine and dehydroevodiamine) are serves as substrates, inducers or inhibitors of CYPs. Indian J.Pharm. Educ. 39(2) April - June 2005 However, phytochemicals belonging to the class of AQ, triterpenoids, and flavonoids may interact with CYPs in three ways: as substrates, as an inducers or inhibitors and modulating the expression. Previously herbals were considered as a food ingredient and not an agent of medical standards. The second misconception that the herbals are safe and cannot interact with medicinal drugs should totally be ruled out. Herb-drug interaction may lead to several emergencies in clinical practise and some may be more fatal that the complications resulted from drug-drug interaction. Herbal products are not subjected to proper scientific testing and no proper awareness is available among practitioners and patients for herbal safety and herb-drug interaction. Clearly, the notion that phytochemicals are problem-free is incorrect, and therefore some degree of regulation is desirable. References 1. Ames B N and Gold L S, The prevention of cancer, Drug Metabolism Reviews, 30, 1998, 201-23. 2. Pantuck E J…et. al., Stimulatory effects of vegetables on intestinal drug metabolism in the rat, J Pharmacol Exp Therap, 198, 1976, 278-283. 3. Ioannides C, Pharmacokineitc interactions between herbal remedies and medicinal drugs, Xenobiotica, 32, 2002, 51-78. 4. Fugh-Berman A, Herb and drug interaction, Lancet, 355, 2000, 13438-45. Maheo K….et al, Inhibition of cytochrome P-450 and induction of glutathion S-transferase by sulphoraphane in primary human and rat hepatocytes, Cancer Res, 57, 1997, 3649-52. 5. 6. Cashmen J R….et al, In vitro and in vivo inhibition of human flavin-containing monooxygenase form 3 (FMO3) in the presence of dietary indoles, Boichem Pharmacol, 58, 1999,1047-55. 7. Katchamart…et. al., Concurrent flavin-containing monooxygenase down-regulation and cytochrome P-450 induction by dietary indoles in the rat: implications for drug-drug interaction, Drug Metab Dispo, 28, 2000, 930-936. 8. Ambudkar….et. al., Biochemical, cellular, and pharmacological aspects of the multi-drug transporter, Annu Rev Pharmacol Toxicol, 39, 1999, 361-98. 9. Schinkel….et al., Absence of the mdr1a pglycoprotein in mice affects tissue distribution and pharmacokinetics of dexamethasone, digoxin, and cyclosporin, A. J. Clin. Invest, 96, 1995, 1698-1705. 10. Sparreboom A….et al., Limited oral bioavailability and active epithelial excretion of paclitaxel (Taxol) 77 caused by p-glycoprotein in the intestine, Proc Natl Acad Sci, 94, 1997, 2031-5. 11. Hunter J and Hirst BH, Intestinal secretion of drugs: the role of P-glycoprotein and related drug efflux systems in limiting oral drug absorption, Adv Drug Deliv Rev, 25, 1997, 129-57. 12. Leslie….et al., Modulation of multi-drug resistant protein 1 (MRP1/ABCC1) transport and ATPase activities by interaction with dietary Flavonoids, Mol Pharmacol, 59, 2001, 1171-80. 13. Van Tellingen O, The importance of drug transporting P-glycoproteins in toxicology, Toxicol Letters, 120, 2001, 31-41. 14. Durr D…et al., St John’s wort induces intestinal Pglycoprotein/MDR1 and intestinal and hepatic CYP3A4, Clin Pharmacol Ther, 68, 2000, 598-604. 15. Sawada…et al., Inhibition of vinblastine efflux mediated by P-glycoprotein by grapefruit juice components in coca-2 cells, Biol Pharm Bull, 21, 1998, 1062-6. 16. Ioannides C, Xenobiotic metabolism and bioactivation by cytochrome P-450. In H. Wiseman, P. Goldfarb, T. Ridgway and A. Wisean (eds), Biomolecular Free Radical Toxicity: Causes and Prevention ,Chichester:Wiley, 2000, 103-44. 17. Guengerich F P, Cytochrome P-450 3A4: regulation and role in drug metabolism, Ann Rev Pharmacol and Toxicol, 39, 1999, 1-17. 18. Ciolino H P, Daschner P J and Yeh G C, Dietary flavonols quercetin and kaempferol are ligands of aryl hydrocarbon receptor that affect CYP1A1 activity, Biochem J, 340, 1999, 715-22. 19. Burchell….et al., The structure and function of the UDP-glucuronosyltransferase gene family, Adv Pharmacol, 42, 1998, 335-8. 20. Tukey R H and Strassburg C P, Human UDPglucoronosyltrasferase: metabolism, expression, and disease, Ann Rev Pharmacol Toxicol, 40, 2000, 581616. 21. Rendic S and Di Carlo FJ, Human cytochrome P450 enzyme: a status report summarizing their reactions, substrates, induction, and inhibitors, Drug Metab Rev, 29, 1997, 413-580. 22. Shimada….et al., Interindividual variations in human liver cytochrome P450 enzymes involved in the oxidation of drugs, carcinogens and toxic chemicals, J Pharmacol Exp Ther, 270, 1994, 414-3. 23. Bertz R J and Granneman G R, Use of in vivo and in vitro data to estimate the likehood of metabolic pharmacokinetic interactions, Clin Pharmacokinet, 32, 1997, 210-58. 78 24. Li A P, Screening for human ADME/Tox drug properties in drug discovery, Drug Discov Today, 6, 2001, 357-66. 25. Lin J H and Lu A J, Inhibition and induction of cytochrome P450 and the clinical implications, Clin Pharmacokinet, 35, 1998, 361-90. 26. Vang O, Jensen M B and Autrup H, Induction of cytochrome P0450IA1, IA2, IIB1 and IIE1 by broccoli in rat liver and colon, Chemico-Biological Interactions, 78, 1991, 85-96. 27. Vang O, Jensen MB and Autrup H, Induction of cytochrome P0450IA1 in rat colon and liver by indole-3-carbinol and 5,6-benzoflavon. Carcinogenesis, 11, 1990, 1259-63. 28. De Kruif…et al., Structural elucidation of acid reaction products of indol-3-carbinol: detection in vivo and enzyme induction in vitro, ChemicoBiological Interactions, 80, 1991, 303-15. 29. Stresser D M, Bailey G S and Williams D E, Indole3-carbinol and b-napthoflavone induction of aflatoxin B1 in the rat, Drug Metab Dispo, 22, 1994, 383-91. 30. Ishizaki…et al., Effect of phenethyl isothiocyanate on microsomal N-nitrosodimethylamine (NDMA) metabolism and other monooxygenase activities, Xenobiotica, 20, 1990, 255-64. 31. Barcelo….et al., CYP2E1-mediated mechanism of anti-genotoxicity of the broccoli constituent sulforaphane, Carcinogenesis, 17, 1996, 277-82. 32. Baron J J and Roberts H R, Caffein consumption, Food and Chemical Toxicology, 34, 1996, 119-29. 33. Cai…et al., Inhibition and inactivation of murine hepatic ethoxy- and pentoxyresorfin O-dealkylase by naturally occurring coumarins, Chem Res Toxicol, 6, 1993, 872-9. 34. Koenigs L L and Trager W F, Mechanism-based inactivation of cytochrome P450 2A6 by furanocoumarins, Biochem, 37, 1998, 10047-61. 35. Haber….et al., Modification of hepatic drug metabolizing enzymes in rat fed naturally occurring allyl sulphides, Xenobiotica, 24, 1994, 169-82. 36. Bajad…et al., Antidiarrhoeal activity of piperine in mice, Planta Med, 67, 2001, 284-7. 37. Stohr J R, Xiao P G and Bauer R, Constituents of Chinese piper species and their inhibitory activity on prostaglandin and leukotriene biosynthesis i n vitro, J Ethnopharmacol, 75, 2001, 133-9. 38. Zhou…et al., Paxton W. Interaction of herbs with cytochrome P450, Drug Metab Reviews, 35, 2003, 35-98. 39. Tsukamoto S, Cha BC and Otha T, Dipiperamides A, B, and C: bisalkaloids from white pepper piper Indian J.Pharm. Educ. 39(2) April - June 2005 nigrum inhibiting CYP3A4 activity, Tetrahedron, 58, 2002, 1667-71. 40. Bano….et al., The effect of piperine on pharmacokinetics of phenytoin in healthy volunteers, Planta Med, 53, 1987, 568-9. 55. Liu J, Liu Y P, Parkinson A and Klaassen C D, Effect of oleanolic acid on hepatic toxicant-activating and detoxifying systems in mice, J Pharmacol Exp Ther, 275, 1995, 768-74. 41. Bano….et al., Effect of piperine on bioavilability and pharmacokinetics of propranolol and theophylline in healthy volunteers, Eur J Clin Pharmacol, 41, 1991, 615-17. 56. Mueller S O, Stopper H and Dekant W, Biotransformation of anthraquinones emodin and chrysophanol by cytochrome P450 enzymesbioactivation to genotoxic metaboites, Drug Metab Dispos, 26, 1998, 540-46. 42. Dixon R A and Steele C, Flavonoids and isoflavonoids- gold mine formetabolic engineering, Trend Plant Sci, 4, 1999, 394-400. 57. Acquaviva R…et al., Antioxidant activity and protective effect on DNA cleavage of reseratrol, J Food Sci, 67, 2002, 137-41. 43. Canivence-Lavier M C….et al., Differential effects of nonhydroxylated flavonoids as inducers of cytochrome P450 1A and 2B isozymes in rat liver, Toxicol Appl Pharmacol, 136, 1996, 348-53. 44. Ciolino H P and Yeh G C, The flavonoid galangin is an inhibitor of CYP1A1 activity and agonist/ antagonist of aryl hydrocarbon receptor, Br J Cancer, 79, 1999, 1340-46. 58. Shukla Y and Taneja P, Anticarcinogenic effect of black tea on pulmonary tumors in Swiss albino mice, Cancer Lett, 176, 2002, 137-41. 45. Ciolino H P, Wang T Y and Yeh G C, Diosmin and diosmetin are agonists of the aryl hydrocarbon receptor that differentially affect cytochrome P450 1A1 activity, Cancer Res, 58, 1998, 2754-60. 46. Shih H, Pickwell G V and Quattrochi L C, Differntial effects of flavonoid compound on tumor-induced activation of the human CYP1A2 enhancer, Arch Biochem Biophys, 373, 2000, 287-94. 47. Kohn….et al., Physiological modeling of a proposed mechanism of enzyme induction by TCDD, Toxicology, 162, 2001, 193-208. 48. Kang C, Tsai S J and Lee H, Quercetin inhibits benzo(a)pyrene-induced DNA adduct in human Hep G2 cells by altering cytochrome P-450 1A1 expression, Nutr Cancer, 35, 1999, 175-79. 49. Bailey….et al., Grapefruit-felodipine interaction: effect of unprocessed fruit and probable active ingredients, Clin Pharmacol Ther, 68, 2000, 468-77. 50. Kane G C and Lipsky J J, Drug-grapefruit juice interactions, Mayo Clin Proc, 75, 2000, 933-42. 51. Sahi J….et al., The effect of bergamottin on diazepam plasma levels and P450 enzymes in beagle dogs, Drug Metab Disp, 30, 2002, 135-40. 52. Connolly J D and Hill R A, Triterpanoids, Natl Product Rep, 14, 1997, 661-79. 53. Lacailledubois M A and Wagner H, A review of the biological and pharmacological activities of saponins, Phytomedicine, 2, 1996, 363-86. 54. Jeong H G, Suppression of constitute and inducible cytochrome P450 gene expression by alpha-hederin in mice, Biochem Mol Biol Intl, 46, 1998, 1019-26. Indian J.Pharm. Educ. 39(2) April - June 2005 59. Zdunczyk Z….et al., Biological activity of polyphenol extracts from different plant sources, Food Res Intl, 35, 2002, 183-86. 60. Bu-Abbas A….et al., Modulation of hepatic cytochrome P450 activity and carcinogen bioactivation by black and decaffeinated black tea, Environ Toxicol Pharmacol, 7, 1999, 41-7. 61. Stupans I., Stretch G and Hayhall P, Olive oil phenols inhibit human hepatic microsomal activity, J Nutr, 130, 2000, 2367-70. 62. Ahn D…et al., The effects of dietary ellagic acid on rat hepatic and esophageal mucosal cytochromes P450 and phase II enzymes, Carcinogenesis, 17, 1996, 821-28. 63. Pelkonen O…et al., CYP2A6: a human coumarin 7hydroxylase, Toxicol, 144, 2000, 139-47. 64. Asano T, Metabolism of ipecac alkaloids cephaeline and emetine by human hepatic microsomal cytochrome P450s, and their inhibitory effects on P450 enzyme activities, Biol Pharm Bull, 24, 2001, 678-82. 65. Ueng Y F… et al., The alkaloid rutaecarpine is a selective inhibitor of cytochrome P450 1A in mu\ouse and human liver microsomes, Drug Metab Dispos, 30, 2002, 349-53. 66. Ernst E, Second thoughts about safety of St. John’s Wort, Lancet, 354, 1999, 2014-16. 67. Moore L B…et al., St. John’s Wort induces hepatic drug metabolism through activation of the pregnane X receptor, Proc Natl Acad Sci USA, 97, 2000, 7501107. 68. Mahajani S S…et al., Some observations on the toxicity and anti-pyretic activity of crude and processed aconite roots, Planta Med, 56, 1990, 665. 69. Fahrenbach M J….et al., Hypocholesterolemic activity of mucilaginous polysaccharides in white 79 leghorn cockerels, Proc Soc Exp Biol Med, 123, 1966, 321. 70. Eda A, Chinese traditional and herbal drugs communications, Fushun Fourth Hospital, 1, 1972, 37. 1995), Drug Safety, 17, 1997, 34256. 86. Ellis G R and Stephens M R, Untitled (photograph and brief case report), Brit Med J, 319, 1999, 650. 87. Page R L and Lawrence J D, Potentiation of warfarin by dong quai, Pharmacotherapy, 19, 1999, 87076. 71. Blumenthal M, Interactions between herbs and conventional drugs: introductory considerations, Herbalgram, 49, 2000, 52-63. 88. McRae S, Elevated serum digoxin levels in a patient taking digoxin and Siberian ginseng, Can Med Assoc J, 155, 1996, 29395. 72. Ishihara K….et al., Interaction of drugs and Chinese herbs: pharmacokinetic changes of tolbutamide and diazepam caused by extract of Angelica dahurica, J of Pharmacy and Pharmacology, 52, 2000, 1023-29. 89. Dai Y R and Yin Y, Inhibition of MAO B activity by Chinese medicinal materials, Chinese Journal of Geriatrics, 6, 1987, 27–30. 90. Burnham B E, Garlic as a possible risk for postoperative bleeding, Plast Reconstruc Surg, 95, 1995, 213. 73. Miller L G, Herbal medicinals: Selected clinical considerations focusing on known or potential drugherb interactions, Archives Internal Medicine, 158, 1998, 2200-11. 74. Deahl M, Betel nut-induced extrapyramidal syndrome: an unusual drug interaction, Mov Disord, 4, 1998, 330-33. 75. Taylor R H, Al-Jarad N and John L E, Betel-nut chewing and asthma, Lancet, 339, 1992, 113436. 76. Gabor M, Pharmacological effects of flavonoids on blood vessels, Angiologia, 9, 1972, 355-74. 77. Cometa M F….et al., Preliminary studies on cardiovascular activity of viburnum prunifolium L. and its iridoid glucosides, Fitoterpia suppli, 5, 1998, 23. 78. Pugsley M K…et al., The cardiac electrophysiological effects of sparteine and its analogue BRB-I-28 in the rat, Eur J Pharmacol, 27, 1995, 219-327. 79. Brinke F, Herb contraindications and drug interactions, Sandy, Ore, Eclectic, 1998,7-41. 91. German K, Kumar U and Blackford H N, Garlic and the risk of TURP bleeding, Br J Urol, 76, 1995, 518. 92. Rose K D….et al., Spontaneous spinal epidural hematoma with associated platelet dysfunction from excessive garlic consumption: a case report, Neurosurgery, 26, 1990, 88082. 93. Brady J F…et al., Inhibition of cytochrome P450 2E1 by diallyl suphide and its metabolites, Chemical Research in Toxicology, 4, 1999, 642-47. 94. Chung K F….et al., Effect of a ginkgolide mixture (BN 52063) in antagonizing skin and platelet responses to platelet activating factor in man, Lancet, 1987, 24850. 95. Lamant V…et al., Inhibition of the metabolism of platelet activating factor (PAF-acether) by three specific antagonists from Ginkgo biloba, Biochem Pharmacol, 36, 1987, 274952. 80. Foldeak S… et al., Acta univ szeged, Acta Phy Chem, 10, 1964, 91. 96. Rosenblatt M and Mindel J, Spontaneous hyphema associated with ingestion of ginkgo biloba extract, N Engl J Med, 336, 1997, 1108. 81. Skidmore-Roth L…et al., Mosby’s handbook of herbs and natural supplements, St. Louise: Harcourt Health Sciences, 1964, 174-75. 97. Rowin J and Lewis S L, Spontaneous bilateral subdural hematomas associated with chronic Ginkgo biloba ingestion. Neurology, 46, 1996, 177576. 82. Sheen L Y….et al., Effect of garlic active principle, diallyl disulfide, on cell viability, lipid peroxidation, glutathione concentration and its related enzyme activities in primary rat hepatocytes, Am J Chin Med, 27, 1999, 95-106. 98. Vale S, Subarachnoid haemorrhage associated with ginkgo biloba, Lancet, 1998, 352. 83. Hatch R C, Effects of other drugs on catnip-induced pleasure behaviour in cats, Am J Vet Res, 33, 1972, 143-55. 84. Viola H….et al., Apigenin, a component of Matricaria recutita flowers, in a central benzodiazepine receptors-ligand with anxiolytic effects, Planta Med, 81, 1995, 213-16. 85. Shaw D….et al., Traditional remedies and food supplements: a five year toxicological study (199180 99. Matthews M K, Association of Ginkgo biloba with intracerebral hemorrhage, Neurology, 50, 1998, 1933. 100. De Smet P M and D’Arcy P F, Drug interactions with herbal and other non-toxic remedies. In: D’Arcy P F, McElnay J C, Welling P G, eds. Mechanisms of drug interactions, Berlin: Springer-Verlag, 1996, 4587. 101. Janetzky K and Morreale A P, Probable interaction between warfarin and ginseng, Am J Health Syst Pharm, 54, 1997, 69293. 102. Shader R I and Greenblatt D J, Phenelzine and the Indian J.Pharm. Educ. 39(2) April - June 2005 dream machine-ramblings and reflections, J Clin Psychopharmacol, 5, 1985, 65. 103. Jones B D and Runikis A M, Interaction of ginseng with phenelzine, J Clin Psychopharmacol, 7, 1987, 201-02. 104. Lee F C…et al., Effects of Panax ginseng on blood alcohol clearance in man, Clin Exp Pharmacol Physiol, 14, 1987, 543-46. 105. Lantz M S, Buchalter E and Giambanco V, St John’s Wort and antidepressant drug interactions in the elderly, J Geriatr Psychiatr Neurol, 12, 1999, 710. 106. Aslam M and Stockley I H, Interaction between curry ingredient (karela) and drug (chlorpropamide), Lancet, 1, 1979, 607. 107. Chen M F…et al., Effect of glycyrrhizin on the pharmacokinetics of prednisolone following low dosage of prednisolone hemisuccinate, Endocrinol Jpn, 37, 1990, 331-41. 108. Demott K….et al., St John’s wort tied to serotonin syndrome, Clin Psychiatry News, 26, 1998, 28. 109. Bon S, Hartmann K and Kuhn M, Schweitzer Apothekerzeitung, 16, 1999, 535-36. 110. Ruschitzka F…. et al., Acute heart transplant rejection due to St John’s Wort, Lancet, 355, 2000, 548-549. 111. Piscitelli S C….et al., Indinavir concentrations and St John’s Wort, Lancet, 355, 2000, 547-548. 112. Von Moltke L L….et al., Triazolam biotransformation by human liver microsomes in vitro: effects of metabolic inhibitors and clinical conformation of a predicted interaction with ketoconazole. Journal of Pharmacol, And Exp Therap, 276, 1996, 370-379. Indian J.Pharm. Educ. 39(2) April - June 2005 113. Yue Q Y, Bergquist C and Gerden, B, Safety of St. John’s Wort (Hypericum perforatum), Lancet, 355, 2000, 576-577. 114. Olesen O V and Linnet K, Metabolism of tricyclic antidepressant amitriptyline by cDNA-expressed human cytochrome P450 enzymes, Pharmacology, 55, 1997, 235-243. 115. Mustapha A, Yakasai I A and Aguye I A, Effect of Tamarindus indica L on the bioavailability of aspirin in healthy human volunteers, Eur Drug Metab Pharmacokinet, 21, 1996, 223-26. 116. Bos R…et al., Valeriana species. Adverse effects of herbal drugs, Berlin:Springer, 3, 1997, 16580. 117. Dandekar U P… et al., Analysis of clinically important interaction between phenytoin and Shankhapushpi, an Ayurvedic preparation, J Ethnopharm, 35, 1992, 285-88. 118. Gordon J B, SSRIs and St John’s wort: possible toxicity?, Am Fam Phys, 57, 1995, 950. 119. Henderson C L…et al., Effect of genseng compounds on cDNA expressed cytochrome P450 enzyme catalytic activity, Life Sciences, 65, 1999, 209-214. 120. Nebel A….et al., Potential metabolic interaction between St. John’s Wort and theophylline, Annals of Pharmacotherapy, 33, 1999, 502. 121. Teelucksingh S…et al., Potentiation of hydrocortisone activity in skin by glycyrrhetinic acid, Lancet, 355, 1990, 1060-63. 122. Paolini M…et al., Effect of liquorice and glycyrrhizin on rat liver carcinogen metabolizing enzymes, Cancer Letters, 145, 1999, 35042. 81 Pharm. Education Need of Upgradation of Diploma in Pharmacy Curriculum Mehta Nikhil K, Asnani Alpana, Pathak Ajay V and Rabra Vandana J.L. Chaturvedi College of Pharmacy, Nagpur Received on 15.5.2004 Modified on 16.9.2004 Accepted on 25.11.2004 ABSTRACT In order to meet international standards, our country has to take steps for the improvement of Pharmacy education system. The proposed paper “Need of Upgradation of Diploma in Pharmacy curriculum” looks into the matter that diploma course should not be abolished rather upgraded. Revision of Pharmacy curriculum, in terms of upgradation is essential. The present study considers the lacunae in the existing Diploma in Pharmacy courses and suggests various measures to upgrade it. In addition, the study advocates that diploma in pharmacy should not be abolished. INTRODUCTION RESULTS AND DISCUSSION Under the provision of Pharmacy Act-1948, Pharmacy Council of India after approval from Central Government made the regulations that prescribes minimum standard of education required for Pharmacist. These regulations were called as Education Regulation (ER)1. On the basis of recommendations of WHO Consultative Committee, Pharmacy Council of India and Central Government have proposed to abolish Diploma in Pharmacy Course in the country and advocate that, Degree in Pharmacy should be considered as the minimum qualification for registration as Pharmacist (ER-2001) 2. Although, the complete Education Regulation is of significance, the present study considers only few significant norms and thereby this could be considered as the limitations of the study. The norms considered are: This has been a matter of opinion that diploma course in Pharmacy should be abolished and degree in Pharmacy should be considered the eligibility for dispensing chemist. The experienced survey conducted among 100 professionals in the field of Pharmacy reveals that the up gradation of curriculum of Diploma in Pharmacy should be given consideration rather than abolishing the curriculum. Therefore, the considered hypothesis has been rejected. The emphasis has been given on the upgradation generally because the individuals opined that diploma in Pharmacy provides faster employment and entrepreneurship. Unless, prescription authorities are given to retail pharmacist, there is no meaning in upgrading the requirements of eligibility of practicing pharmacy from diploma to degree. However, during the survey the following shortcomings have been observed in the existing Diploma in Pharmacy curriculum. 1. 2. Nature and period of course Nature and period of practical training to be undertaken after the completion of regular course (not less than 750 hours) covered in a minimum of three months in an institution, hospital, pharmacy or dispensary recognized by Pharmacy Council of India. 1. Analysis taught has no practical values. 2. Outdated compounding. 3. Allied subjects like Drug Store & Business Management and Pharmaceutical Jurisprudence have been limited only up to theoretical considerations. METHODOLOGY3 4. Lack of Industry - Institute interactions. The area for the present study has been considered as Nagpur. Experienced survey was done of concerned Pharmacists (inclusive of retail chemist, teachers, diploma and degree students of pharmacy). The total sample size was taken as 100 and the time of the study was academic year 2002-2003. The limitations of the study have already been mentioned. The research design has a specific nature of process of Demand characteristics. Mean value of opinion has been considered and statistical test has been applied to check the hypothesis “Abolition of Diploma Course in Pharmacy is the effective method to raise the standards of Pharmacy education”. The hypothesis has been interpreted and conclusions have been made. The present study is suggestive in nature. 5. Lack of Hospital - Institute interactions. 6. Lack of Market - Institute interactions. 7. Practical training of 750 hours not up to the mark. 8. Lack of modernity and technical up-gradations in many institutes. 9. Lack of professionalism in the professional course (B.Pharm) and Diploma holders. 3. 82 The subjects of the examination and the standards attained therein. 10. Lack of Spirit of Entrepreneurial Development in the curriculum. During the survey, when asked to the respondents the following suggestions have been observed and they are opined below. Indian J.Pharm. Educ. 39(2) April - June 2005 1. 2. 3. Lack of professionalism has been a curse to retail chemist and most of the times they are compared with Grocery walas. If it has been made mandatory on the part of retail/wholesale chemist to have their own quality control in their retail / wholesale outlets, the significance of analysis taught to them would be increased and the responsibility of controlling and assuring the quality of product sold by them would be extended to retailers / wholesalers from manufacturers. Also, it would offer an employment to others, who cannot afford to start their own outlets and the quality system in the country pertaining to pharmaceutical products and services will be upgraded. Compounding of old traditional medications4 should be extended to compounding of medications containing new molecules, dosage forms like aerosols, and Ayurvedic preparations (considering product patent regime from year 2005 onwards) so that the chemist will be benefited with the advanced knowledge. Likewise, Synthesis of newer molecules should be added to the curriculum. The syllabus in this context should be revised with quicker frequencies. Allied Subjects like Drug Store and Business Management and Pharmaceutical Jurisprudence are restricted to theoretical considerations because of various reasons: · Teachers during their graduation or post graduation do not have adequate orientation regarding these subjects. Mere passing paper of 100 marks is not sufficient for teaching these subjects. · No appropriate allocations or eligibility criteria made for teacher specialization in M.Pharm (Pharmaceutical management) or MBA or M. Pharm (Quality Assurance) have been made, leading to lack of orientation of such subjects among the student. market- institute interactions. ER-91 which states about “nature and period of practical training to be undertaken after the completion of regular course” needs modification. This training should be made mandatory in between first and second year of the curriculum (as in the case of B. Pharmacy where industrial training can be done after third year of the course).6 There should be compulsory preparation and submission of report of training by the student and viva voce be considered the norms for examining the candidate. The Committee be constituted for the purpose of examining these candidates which should be comprising of: · Teacher of Drug Store and Business Management, Pharmaceutical Jurisprudence or Hospital and Clinical Pharmacy of the institute of candidate as the case may be depending upon the type of training in market, industry or hospital be the internal examiner. · Teacher of Drug Store and Business Management, Pharmaceutical Jurisprudence or Hospital and Clinical Pharmacy of the other institute as the case may be depending upon the type of training in market, industry or hospital be the external examiner. · Any Retail or Hospital Pharmacist or Industrial pharmacist as the case may be as an expert. · Institute should have to supply the list of their candidates undergoing training to Pharmacy Council of India and MSBTE depending upon which surprise visits can be held by Inspector of State Pharmacy Council or Executive Committees. The trainer (from retail, industry or hospital as the case may be) are made to submit their reports in the prescribed format7 (suggested along with the present paper) to the institutes and which could be taken as one of the tool for evaluating candidates performance. · Communication Skills and Professional English and Entrepreneurial Development should be added as the subjects in the curriculum to raise the standards of individuals. The question cropped up during the interview was why retailers, industry or hospital be interested in being a part of training? The application of Victor Vroom’s Theory of Motivation8,9 solves the problem i.e. “person does the things in which he foresee his advantage”. Government of India should take the step for increasing interest of the retailers, industry or hospital in training by availing concessions in income tax as a rebate per candidate trained or certain kind of monetary benefits provided by the sharing of institute, PCI, MSBTE and Government of India. The remuneration as best training centre can also be one of the motivating factors. The extension of these subjects can be done by increasing industry-institute, hospital-institute and Thus, the upgraded diploma in pharmacy would yield faster employment and promote entrepreneurship. · Lack of Spirit of Entrepreneurial Development in the curriculum of Drug Store and Business Managements.5 Indian J.Pharm. Educ. 39(2) April - June 2005 83 Suggestive Format for Trainers (to submit their reports to Principal of the Institute) Name and Address (Place of training) Name of the Candidate : .............................................................................................................. Name of the Institute : .............................................................................................................. Name of the Trainer : .............................................................................................................. Registration no.of Trainer : .............................................................................................................. Place of Training : .............................................................................................................. Address : .............................................................................................................. Telephone No. : .............................................................................................................. E-mail : .............................................................................................................. I) Please evaluate the performance of candidate (out of 3) in each case: 1. Learning Capability: 2. Alertness: 3. Initiativeness: 4. Technical Knowledge: 5. Behaviour of Customers: 6. Accounting Skills 7. Legal Knowledge: 8. Inventory Management Skills: 9. Routine Working Skills: 10. Behaviour with inspectors: Total out of 30 : II) Please mention the various contents covered during the training programme. III) Recommendations: Promoted / Not to be Promoted Date: Signature of Trainer (Seal) References 1. Universal Law Publishing Co., Pharmacy Act 1948 with Short notes, Sec 10, 1999, 7. 6. Nagpur University, Nagpur, Faculty of Medicine, Ordinance No. 153, point 22, 4. 2. Bag, M M, Abolition of Diploma Courses, Pharma Academia, Express Pharma Pulse Special Feature, December 18, 2003, 68 Zikmund William, Business Research Method, Singapore:Thomson Asia, 512. 7. Mehta, R.M, Drug Store and Business Management, New Delhi: Vallabh Prakashan, 3rd Ed., 118. 8. 4. Maharashtra State Board of Technical Education, Mumbai Syllabus of Diploma in Pharmacy, 9 9. 5. Maharashtra State Board of Technical Education, Syllabus of Diploma in Pharmacy, 16 Mehta, N. K, Industrial Psychology and Sociology (for First year B. Pharm Students), Nagpur: VBD Publications, 85 Pattanayak Biswajeet, Human Resource Management, Motivational Theories, New Delhi: Prentice Hall of India, 2001, 188. 3. 84 Indian J.Pharm. Educ. 39(2) April - June 2005 Pharm. Chemistry Study of the Dimer of Imipramine Radical as Laboratory Marker for Antioxidant Evaluation M.K. Tripathy*, D.K. Tripathi* and U.N. Dash** *P.G. Department of Pharmaceutics, Sri Jayadev College of Pharmaceutical Sciences, Naharkanta ** Former Director, University Department of Pharmaceutical Sciences, Utkal University, Bhubaneswar Received on 08.06.2004 Modified on 30.11.2004 Accepted on 05.02.2005 ABSTRACT A laboratory marker has been considered as a tool to quantify the in vitro antioxidants property. In this study, considering the non-enzymatic mechanism of antioxidants defense the oxidative reaction of Imipramine (IMP) hydrochloride with Fe (III) ions as the oxidative substance and the response of the reaction to different antioxidants was considered. Vitamin C was used as the reference antioxidant and four different extracts of Terminallia chebulla were used to test their antioxidant potential. The study was based on the hypothesis that, dibenzoazepine undergoes oxidative reaction with formation of coloured products, which can be quantified spectrophotometrically. The study revealed the development of a blue colour, which is because of the dimer resulted due to the dimerization of two-cation radicals, of the oxidized product imipramine, gave chromophores at 670 nm. Vitamin C as an antioxidant being a powerful electron donor reacted with the cation radical and helped to get stabilized and prevent the formation of a coloured dimer as evident by the decrease in absorbance. The different plant extracts also behaved in the same fashion in the reaction mixture and stabilized the radical. As the antioxidants prevent the radicals produced in the system from formation of dimer and the antioxidant activity following the reaction pathway are also accurately measurable on repeat tests, the system is proposed as a novel method and the dimer as a laboratory marker for antioxidant evaluation. INTRODUCTION The role of antioxidants in health and disease is now well recognized. Antioxidants reduce or eliminate the cytotoxic reactive oxygen species (ROS) that are generated in the tissues in several patho-physiological conditions. Biological tissues maintain critical balance between antioxidant reserve and the ROS, which are continuously produced in the cells. In patho-physiological conditions, this balance is upset because of reduction in antioxidants reserve and excess production of ROS, which play a crucial role in many degenerative diseases. The potential for antioxidants therapy therefore continues to grow at a staggering pace1. In this context, much thrust has been given on the phyto constituents having antioxidant activity, hence their screening becomes very important. A laboratory marker has been considered as a tool to quantify the in vitro antioxidant property. In this study, considering the nonenzymatic mechanism2 of antioxidant defence, we envisaged, to study the oxidative reaction of imipramine hydrochloride with Fe (III) ions as the oxidative substance and the response of the reaction to different antioxidants. In this study, vitamin C was used as the reference antioxidant and four different extracts of Terminallia chebulla were used to test their antioxidant potential. The study is based on the hypothesis that the dibenzoazepine derivatives undergo oxidative reaction with the formation of coloured products. The extent of Indian J.Pharm. Educ. 39(2) April - June 2005 formation of coloured product can be quantified spectrophotometrically. In case of imipramine hydrochloride which reacts with Fe(III) ions at higher temperature with formation of a blue coloured product. The progress of reaction depends on the concentration and type of the acid used, concentration of antioxidant, temperature and type of heating. Below is the mechanism of reaction.3 EXPERIMENT Pure imipramine hydrochloride was procured as a gift sample from Torrent Research Centre, Ahmedabad. All 85 other reagents were of Analytical Grade and the solutions were prepared with double distilled water. Forty-five test tubes graduated at 10 ml were divided into 5 groups (A, B, C, D and E). Each group containing 9 test tubes and were marked as T1, T2, …..., T9. Group A represented the reaction module with vitamin C as reference antioxidant4, 5, Group B to E represented the reaction module with the four different extracts of Terminallia chebulla in petroleum ether (40-60), chloroform, alcohol (95 % v/v) and water respectively. In each group one test tube marked as T1 was used as the control where no antioxidant was added and the rest eight test tubes were used for the tests where eight different volumes such as 0.1, 0.2, ……, 0.8 ml with a strength of 500 mg/ml of the different samples were added. In each test tube, one ml of 4 ´ 10-2 mole/litre FeCl3 solution was placed and to that 1.5 ml of 10 mole/litre CH3COOH volume of 1 ´ 10-4 mole/litre imipramine hydrochloride solution was added. In case of control, the total volume was diluted to the mark (10 ml) with distilled water and in case of test sample tubes (T2-T9) the respective volume of test samples were added and the final volume was made up to the mark with double distilled water. The reaction components in each tube were mixed thoroughly with vortex mixer and then heated at 75 ± 0.5o C for 5 minutes in a thermostatically controlled waterbath. After cooling to room temperature, the absorbance of each solution was measured at 670 nm against reagents blank without using imipramine in a Genesys 2 TM Thermo spectronic, double beam U.V visible Spectrophotometer, U.S.A. Preparation of Plant Extracts Dried fruits of Terminallia chebulla were collected locally. They were identified with the help of the Department of Drabya Guna Vigyan, Government Ayurvedic Medical College, Puri, Orissa. The specimens were cut into small pieces, dried at 40-50oC for 48 hours and powdered. The powder weighing 120 g was subjected to successive extraction with petroleum ether (40-60), chloroform, alcohol (95 % v/v) and water using soxhlet apparatus for 8-10 hours. The extracts with different solvents were completely evaporated at 40oC over waterbath and finally under vacuum. The residues 0.380 g for petroleum ether, 1.080 g for chloroform, 8.050 g for ethanol and 1.780 g for water were subjected to antioxidant activity. RESULTS AND DISCUSSION As evidenced from (Table–1 & Fig-1), Group A shows 86 that the absorbance has decreased gradually from 0.433 to 0.048 due to the presence of the antioxidant, vitamin C in an increasing order. This establishes that vitamin C being a powerful electron donor stabilizes the cationic radical of imipramine hence prevents the formation of the dimer, the colored complex. Similarly the gradual decrease in absorbance was found in each of group B, C, D and E which represent the different extracts of Terminallia chebulla in petroleum ether, chloroform, alcohol, water respectively. This indicates that each of these extracts contain a principle having antioxidant property and it can be assumed that the mechanism of action is similar to that of vitamin C, which is a known antioxidant.4 , 5 Since in each of the cases maximum absorbance of 0.433 has been observed when the dimerization of imipramine radical took place under the experimental conditions without any hindrance and if this absorbance is considered to represent 100% dimerization, then reduction of absorbance, i.e. blockade of dimer formation, to 0.048 can be interpreted as 88.92 % antioxidant activity by the standard antioxidant, vitamin C. Table-1 shows that all the four different extracts of Terminallia chebulla represented as group B,C,D and E also reduced the absorbance from 0.433 to 0.142, 0.064, 0.008 and 0.008 respectively. Out of all the five groups, group D and E, i.e.alcoholic and water extracts of Terminallia chebulla showed the maximum antioxidant activity by reducing the absorbance to the minimum of 0.008. When the activity of each group is correlated with the concentration, except the alcoholic extract, all other three extracts and vitamin C showed their maximum activity at a concentration of 40 mg/ml (400 mg in 10 ml), while the alcoholic extract shows its maximum activity at a concentration of 25 mg/ml (250 mg in 10 ml) and it blocks the dimer formation to the extent of 98.15%. Table-2 shows the interpreted results in terms of antioxidant activity. Table-2 also indicates that petroleum ether extract exhibited its antioxidant activity up to 67.20% at a concentration of 40 mg/ml and chloroform extract at the same concentration exhibited its activity up to 85.22%. Both aqueous and alcoholic extracts exhibited better results, that is each of the two could block the dimer formation up to 98.15% and between these two, alcoholic extract showed to be better because at a concentration of 25 mg/ml it was active. The results are shown as an average of 4 repeat experiments where in a good extent of reproducibility was observed as indicated by low standard deviation. Indian J.Pharm. Educ. 39(2) April - June 2005 Table-1: Showing the response of reaction mixture to the addition of antioxidants Test Modules T1 T2 T3 T4 T5 T6 T7 T8 T9 n=4 Group A 0.433 ± 0.014 0.401 ± 0.006 0.388 ± 0.002 0.314 ± 0.017 0.277 ± 0.012 0.186 ± 0.014 0.124 ± 0.008 0.084 ± 0.006 0.048 ± 0.004 Absorbance (Average ± S.D.) Group B Group C Group D 0.433 ± 0.014 0.433 ± 0.014 0.433 ± 0.014 0.403 ± 0.022 0.363 ± 0.014 0.222 ± 0.014 0.389 ± 0.026 0.351 ± 0.012 0.162 ± 0.008 0.376 ± 0.026 0.309 ± 0.008 0.092 ± 0.012 ± ± 0.306 0.019 0.295 0.006 0.044 ± 0.004 0.296 ± 0.017 0.229 ± 0.004 0.008 ± 0.002 0.242 ± 0.030 0.159 ± 0.008 0.196 ± 0.006 0.096 ± 0.006 0.142 ± 0.012 0.064 ± 0.002 Group E 0.433 ± 0.014 0.301 ± 0.010 0.262 ± 0.008 0.214 ± 0.004 0.156 ± 0.006 0.123 ± 0.003 0.094 ± 0.004 0.036 ± 0.002 0.008 ± 0.001 Table-2: Antioxidant activity in terms of % blockade of dimer formation Concentration µg/ml 00 05 10 15 20 25 30 35 40 Group-A 0 07.39 10.39 27.48 36.03 57.03 71.36 80.60 88.91 Group-B 0 06.93 10.16 13.16 29.33 58.43 44.11 54.73 67.20 Group-C 0 16.17 18.94 28.64 31.87 47.11 63.28 77.83 85.22 Group-D 0 48.73 62.59 78.75 89.84 98.15 - Group-E 0 30.48 39.48 50.58 63.97 71.59 78.29 91.68 98.15 Fig. 1 : Showing the response of reaction mixture in different test modules to the addition of antioxidants Indian J.Pharm. Educ. 39(2) April - June 2005 87 CONCLUSION References Different researchers have used different in vitro models to evaluate the antioxidant activity of samples. In this study dimerization of imipramine radical has been taken as the in vitro model and vitamin C as the reference standard. It has been concluded that vitamin C responded to the model following nonenzymatic mechanism and the different extracts of Terminallia chebulla contain antioxidant principle which could block the activity of imipramine radical in a reproducible manner. This model, because of its simplicity and reproducibility is proposed to be a novel method for antioxidant evaluation using the imipramine dimer as the laboratory marker. 1. 2. 3. 4. Acknowledgement One of the authors (M.K.Tripathy) is thankful to the management of Sri Jayadev College of Pharmaceutical Sciences, Naharkanta for encouraging the research activities and providing the necessary facilities for carrying out the research work. 88 5. Das, D, “Antioxidant and Redox Signaling ” Lecture Note, in International Conference on Role of Free Radicals in Health and Disease, Cardiovascular Research Centre, University of Connecticut, School of Medicine, Farmington, USA, Feb. 10-12, 2003. Chatterjee, P, Free radicals in Health and Disease, J. International Medical Sciences Academy, 10, 1999, 231. Karpinska, J and Starczewska B, Reactions in Imipramine-Pyrocatechol – Violet and Imipramine Iron (III) ion Systems, Pharmazie, 54(1), 1999, 41-43. Ray, K, Rudra, S, De, AU, Sengupta, C, Evaluation of Ascorbic acid as an inhibitor of lipid peroxidation induced by Cefotaxime Sodium and Metoprolol, Indian J. Pharm.Sci, 61,1999, 44-47. Patil, S, Jolly C and Narayanan, S, Free radical scavenging activity of Acacia Catechu and Rotula Aquatica: implications in cancer therapy, Indian Drugs, 40(6), 2003. Indian J.Pharm. Educ. 39(2) April - June 2005 Pharm. Marketing Leveraging Through Marketing in Modern Times Manthan J., Udupa N.* Manipal College of Pharmaceutical Sciences, MAHE, Manipal 576 104 Received on 05.08.2004 Modified on 19.10.2004 INTRODUCTION World is undergoing radical changes. Last five decades have seen enormous development. Technological advancement, deregulation, globalization, elimination of trade barriers provides endless opportunities. World is shrinking and so do markets. Change is occurring at a rocketing speed. What is new today may be obsolete tomorrow. Government regulations are liberalized that pave the way for marketing professionals. World has become a global village and products developed in one country are available throughout the world. Marketing is a dynamic field and thus, marketing professionals have to be dynamic too. They constantly need to amend new products, new market segments etc. Demographic shifts are taking place. There is increase in number of old people all around the world and thus, their health concerns need to be addressed. Average life expectancy of people in India was 59 years in 1990s, which has increased to 64 years at present but this is less as compared to US where average life expectancy is 77 years. This is due to awareness regarding health and better medication. Pharmaceutical Marketing One may ponder how Pharmaceutical marketing is different from general marketing. As we know that we do not need a prescription to purchase items of daily livingbe it food, clothes or house. Here the buyer is the sole decider of which product to purchase, when and in what number. But you need a prescription to purchase medicines, which are used to treat certain symptoms or diseases. Thus, the significant difference is that in Pharmaceutical marketing the marketer reaches target consumer through intermediate customer who, in this case, is a doctor. Pharmaceutical marketing deals with a person who is more conversant and knowledgeable in his field. A doctor decides which drug(s) to prescribe for what indication and in what quantity. Buyer has no choice in deciding which drug to buy and which not for a particular illness. Therefore, it is no exaggeration to say that Pharmaceutical marketing is unique. Marketing – an essential part of industry gamut Marketing professionals are accused of creating needs. People always say, “Marketers get people to buy things they don’t want.” As Philip Kotler, a prominent Indian J.Pharm. Educ. 39(2) April - June 2005 Accepted on 29.12.2004 marketing guru, aptly says, “Marketers do not create needs. Needs preexist marketers.” Thus, marketing professionals try to unearth the latent needs of people and cater to those needs, as people themselves are not aware of their needs. An example of Viagra would be the best fit for justification. Pfizer, world’s top Pharmaceutical Company identified the need of people to improve their sexual potential. Though people were interested in buying such product, they were not able to speak candidly. Pfizer found this latent need and leveraged on it. Thus, Pfizer’s product Viagra became a blockbuster and generated more than a billion dollars sale for the company. Another example is that of ranitidine from Glaxo. Through marketing skills, Glaxo was able to generate more than a billion dollars as revenues from the sale of this single product. This product became a blockbuster product. Marketing also depends on the brand image of the product. Companies have strived through the years to create distinct Brand image in the minds of their customers. Once the brand image is created half the battle is won. But it is very difficult to create brand image in this competitive era. Before a company builds a brand image, it has to identify its market, inform decision makers about its profile and give them compelling reasons to care. A successful brand is one, which clearly satisfies physician’s needs. None can deny the role and importance of marketing in Pharmaceuticals. Merely a good product developed by R&D would not suffice to make product a success. Best products developed by R&D have not been able to see the daylight in the marketplace. For example Johnson & Johnson introduced a new sanitary napkin “Modest” in the 70’s to take on the pioneer “Comfit”, which was marketed by competitor. The product of Johnson & Johnson never took off and finally was withdrawn. Another example is from cephalosporins market. So many cephalosporins have been developed but only some molecules have met with the success in the marketplace due to sustained marketing efforts made by companies. Cefprozil is one among such cephalosporins that never really was accepted in the market. No matter how good your product is, it would not be a success if marketing department of a company were fragile. You need a sharp mind to leverage on a good product developed by R&D. 89 As Charles Revson of Revlon observed: “ In the factory, we make cosmetics; in the store we sell hope.” This is true in our context also. A pharmaceutical company makes medicines in their factory but sell hope; hope of healthy living, hope of life in case of life threatening diseases like AIDS and Cancer. The responsibility lies on the professionals not to shatter this hope. In addition, the responsibility of Pharma marketing professional is that he should not play with the life of people by simply marketing a good for nothing product. Marketing Interface Marketing interface builds an image for the company – a corporate image as we call it. The task of marketer simply does not end here. Marketing works in tandem with other departments of a company; in fact, activities of other departments depend on the marketing department. Marketing department has to deal with internal as well as external environment. (See Fig.1). Marketing department gives the data on future requirements of market based on which the production department sets out its schedule. It also collects feedback from market and gives information regarding changes in dosage form, packaging, strength of a product, texture, color and flavor in case of liquid dosage forms, method of administration of drugs, change in salt of molecule. Based on this information R&D department initiates its activities to modify existing product and meet the market requirements. Marketing also works in tandem with distribution and logistics department of the company, as availability of drugs in market place is also important. Time is one of the important factors in marketing activity. Earlier you are in the market, more are the benefits. People remember names of those who are the first in their field. Ask what is the name of the first person to fly solo across the North Atlantic? The answer is Charles Lindbergh. Ask the name of the second person. Few can remember. Therefore, time factor plays a pivotal role in marketing. It is generally said that if you want win the marketing battle, you need to be first in the market. But this may not always be applicable to pharmaceutical marketing. With more than 80,000 odd pharmaceutical brands and new products added at breakneck speed, it is necessary for Indian companies to clearly differentiate their products with that of competitors. The key here is product differentiation, which helps company to create competitive advantage over competitors and establish the product even if the company is late entrant in the market for a particular product or therapeutic segment. Marketing in general and pharmaceutical marketing in particular has a social responsibility. As pharmaceutical 90 products deals with healthcare of society and provides better hope of healthy living, it is marketers’ prime responsibility to fulfill their obligations. While detailing to doctors regarding the products, representative of the company should bear in mind that they have to be judicious in detailing of the product since, wrong product or product information to the doctors can be fatal for the patient. Responsibility to inculcate these virtues lies with the marketing department of the companies and companies should devise a strategy to implement this to its bottom level i.e. to the representative level. Once company’s image is established as a provider of authentic information, half the battle is won to capture market share. It is generally observed that currently almost all the companies are following niche marketing to grab the maximum market share and therefore are creating divisions catering to the needs of doctors for various therapeutic segments. This helps them to be focused and allocation of the resources can be justified. Future Marketing is also undergoing radical changes and newer techniques are developed by the companies to increase their reach to the doctors. E-detailing is one such concept developed by the companies. Here rather than face to face conversation with doctors, doctors are contacted through web based virtual detailing where doctors can interact on the web. This method saves the money and busy doctors can access the information regarding drugs at any time, depending on their convenience. But this concept is still not developed in India unlike United States. Further, Customer Relation Management has become buzzword in the industry. Companies are striving to retain customers rather than increasing their customer base. This also provides companies endless opportunities to grow in their business. Summary In a nutshell, it can be said that the role of marketing cannot be ignored in this fiercely competitive world where companies are vying with one another to gain better market share. Lose your focus and you are out of the arena and there is someone to replace you. So, in these turbulent times where companies are finding it difficult to survive, let alone grow, companies should leverage on marketing as an essential tool. “Companies should think of millennium as an opportunity to increase mindshare and heartshare.” Philip Kotler Indian J.Pharm. Educ. 39(2) April - June 2005 Internal External Doctors Research and Research and development development Production Trade organizations Materials Management Distribution Channels Public Public Relations Department Relations Patients MARKETING Finance Department Government Advertising Advertising Agency Agency Marketing Research Department Fig 1 : Internal and External Marketing Interface References 1. Subba Rao, S.V.R., The Product, In: Handbook of Pharmaceutical Marketing in India, Panther Publishers, 1998, 3.1 to 3.3. 2. Ries Al, Trout Jack, Getting into the mind, In: Positioning - The battle for your mind, McGraw Hill, 2001, 19. Lidstone John, and Collier Terry, Product Review, In: Marketing Planning for the Pharmaceutical Industry, Gower, 51. 3. Indian J.Pharm. Educ. 39(2) April - June 2005 4. 5. 6. Kotler Philip, Understanding Marketing Management-Marketing in the twenty first century, In: Marketing Management, Prentice Hall India, 2000, 1-25. Smarta Raja, New Marketing Approaches, In: Revitalizing the pharmaceutical market, Response books, 1999, 43. Davidson Terry and Sivadasa Eugene, Details Drive Success, Marketing Health Services, spring 2004, 20-25. 91 Pharm. Biotechnology Ribozymes: The Trans Acting Tools for RNA Manipulation A. Nayak, and D. V. Kohli* Department of Pharmaceutical Sciences, Dr. Hari Singh Gour Vishwavidyalaya, Sagar-470 003 Received on 14.08.2004 Accepted on 22.01.2005 ABSTRACT Ribozymes are small and versatile nucleic acids that can cleave RNAs at specific sites. Ribozymes have enormous potential in basic research and biotechnology with special promise for applications in human medicine. In this context, a catalytic RNA is designed to specifically recognize, interact with, and alter a target molecule. These molecules have great potential to be used as effective gene therapeutic agents. The best-characterized ribozymes are hydrolytic nucleases that perform site-specific cleavage of a target RNA. The ability of ribozymes to recognize and cut specific RNA molecules makes them exciting candidates for human therapy. Ribozymes can be used both to down regulate and repair pathogenic genes that may lead to disease conditions. In some instances, short-term exogenous delivery of stabilized RNA is desirable, but many treatments will require viral-mediated delivery to provide long-term expression of the therapeutic catalyst. Current gene therapy applications employ variations on naturally occurring ribozymes. INTRODUCTION Until about 20 years ago, all known enzymes were proteins. But then it was discovered that some RNA molecules can act as enzymes; that is, catalyze covalent changes in the structure of substrates (most of which are also RNA molecules). Catalytic RNA molecules are called ribozymes. A ribozyme can be thought of as a chimeric RNA molecule consisting of two stretches of antisense RNA (AR) flanking a nucleolytic motif. The AR component, referred below as the flanking complementary regions (FCRs), provide the target selectivity. Two generic types have been exploited, the “hammerhead” ribozyme 8 and the “hairpin” ribozyme 9 . Both can cleave GUC sites, but the hammerhead can also cleave at GUA, GUU, CUC and UUC with comparable efficiency10 and sometimes at AUC11, 12. Types of Ribozymes Five classes of ribozymes have been described based on their unique characters in the sequences as well as threedimensional structures. They are denoted as (i) the Tetrahymena group I intron, (ii) RNase P, (iii) the hammerhead ribozyme (Fig.1), (iv) the hairpin ribozyme, and (v) the hepatitis delta virus ribozyme. They may catalyze selfcleavage (intramolecular or “in-cis” catalysis) as well as the cleavage of external substrates (intermolecular or “in-trans” catalysis). Fig 1: Hammerhead Ribozyme Self-splicing group I introns catalyze their excision and the ligation of flanking exon sequences via two sequential transesterification reactions13. Group I introns from T4 phage14 and Tetrahymena thermophila15,16 have been bisected, and the separated components have been coexpressed in various cell types. Formation of natural base pairings and presumably, tertiary interactions between the two components in vivo resulted in transsplicing reactions analogous to the naturally occurring cis-splicing reactions. Demonstration that the Tetrahymena ribozyme catalyzes the ligation of exons in trans has led to speculation that these molecules could 92 be used for therapeutic repair of defective transcripts 17. Alteration of endogenous myotonic dystrophy protein kinase transcripts and repair of sickle b-globin transcripts by trans-splicing ribozymes in mammalian cells have recently been demonstrated. However, this type of ribozyme interacts with the intended target mRNA via a base-paired helix (P1) of only 6 bp and shows relatively poor specificity, with products of illegitimate splicing seen in vivo18. Mode of Action of Ribozymes The discovery that RNA can act as a biological catalyst, as well as a genetic molecule, indicated that Indian J.Pharm. Educ. 39(2) April - June 2005 as gene inhibitors 20. Ribozyme gene therapy may be used as an adjunct to chemotherapeutic drugs affecting viral suppression, and facilitating immune restoration without problems of patient compliance. RNA enzymes; ribozymes are being developed as treatments for a variety of diseases ranging from inborn metabolic disorders to viral infections and acquired diseases such as cancer. The hammerhead ribozyme, one of the smallest ribozymes identified, is able to induce site-specific cleavage of RNA, with ribozyme and substrate being two different oligoribonucleotides with regions of complementarity. Its ability to down-regulate gene expression through RNA cleavage makes the hammerhead ribozyme a candidate for genetic therapy. This could be particularly useful for dominant genetic diseases by down-regulating the expression of mutant alleles. The group I intron ribozyme, on the other hand, is capable of site-specific RNA trans there was a time when biological reactions were catalysed in the absence of protein-based enzymes. It also provided the platform to develop those catalytic RNA molecules, called ribozymes, as trans acting tools for RNA manipulation. Viral diseases or diseases due to genetic lesions could be targeted therapeutically through ribozymes, provided that the sequence of the genetic information involved in the disease is known 19. In mammalian cells, genetic instructions are usually revised by RNA splicing before they are translated to proteins. A trans-splicing group I ribozyme can be employed to intentionally modify the sequence of targeted transcripts in tissue culture cells. Such analysis should facilitate the logical development of safe, therapeutic ribozymes that can repair mutant RNAs associated with a variety of inherited diseases. Ribozymes can be targeted to cleave specific RNAs (Fig. 2), which has led to much interest in their potential 1. Ribozyme joins with RNA message Ribozyme RNA message 2. Ribozyme cuts the RNA message Ribozyme Cut introduced into RNA message 3. A large proportion of the RNA message is cut. Thus a corresponding protein is not produced. Cut cleaved RNA messages Fig 2 : Mode of Action of Ribozyme Indian J.Pharm. Educ. 39(2) April - June 2005 93 -splicing. It can be engineered to replace part of an RNA with sequence attached to its 3' end. Such application may have importance in the repair of mutant mRNA molecules giving rise to genetic diseases. However, to achieve successful ribozyme-mediated RNA-directed therapy, several parameters including ribozyme stability, activity and efficient delivery must be considered. Ribozymes are promising genetic therapy agents and should, in the future, play an important role in designing strategies for the therapy of genetic diseases 21. Applications The possibility of designing ribozymes to cleave any specific target RNA (Fig.3) has rendered them valuable tools in both basic research and therapeutic applications. They have been exploited to target viral RNAs in infectious diseases, dominant oncogenes in cancers and specific somatic mutations in genetic disorders. Most notably, several ribozyme gene therapy protocols for HIV patients are already in Phase 1 trials. More recently, ribozymes have been used for transgenic animal research, gene target validation and pathway elucidation22. Dominant Retinal Degenerative Disease: In dominant forms of retinal degeneration, patients have a healthy functioning gene and a gene with a disease-causing mutation. The mutant gene produces a dysfunctional toxic protein that damages the photoreceptor cell. Ribozymes are molecules containing genetically encoded information that disrupt the mutant gene’s ability to produce the harmful protein. With the diseased gene inactivated, the healthy gene can supply the photoreceptor cell with the needed protein. Cancer: The ability of ribozymes to recognize and cut specific RNA molecules makes them exciting candidates for cancer therapy. Already, a synthetic ribozyme that destroys the mRNA encoding a receptor of Vascular Endothelial Growth Factor (VEGF) is under clinical trials. VEGF is a major stimulant of angiogenesis, and blocking its action may help starve cancers of their blood supply. Hammerhead ribozymes can be of great importance to overcome drug resistance in chemotherapy. These ribozymes targeted the RNA product of the MDR1 gene, the multi-drug resistance gene, and the cells then became sensitive to the antitumor drug, vincristine. The same abstract also described a ribozyme targeting an overexpressed growth factor gene that self- stimulated tumor growth; the ribozyme blocked formation of the growth factor and inhibited cell division. Further studies GUN GUN Binding Next Cycle Cleavage Dissociation GU N GU N Fig 3 : Steps of Ribozyme Action 94 Indian J.Pharm. Educ. 39(2) April - June 2005 with these substances should be interesting and of great importance. Ribozymes expressing prostate cancer cells were characterized by a significant reduction of survivin expression compared to parental cells transduced with a control ribozyme; the cells became polyploid, underwent caspase-9-dependent apoptosis and showed an altered pattern of gene expression, as detected by oligonucleotide array analysis. Survivin inhibition also increased the susceptibility of prostate cancer cells to cisplatin-induced apoptosis and prevented tumor formation when cells were xenografted in athymic nude mice. These findings suggest that manipulation of the antiapoptotic survivin pathway may provide a novel approach for the treatment of androgen-independent prostate cancer23, 30. Retinitis Pigmentosa: A mutant gene calls for the creation of a protein that damages the eye’s light-sensitive rod cells as in transgenic rat model of retinitis pigmentosa containing a dominant rod opsin mutation (proline-tohistidine change at position 23) 24. Viral vectors based on the nonpathogenic human adeno-associated virus, when coupled with the strong rod photoreceptor specific opsin promoter, offer an efficient and nontoxic way to deliver and express ribozymes in photoreceptor cells for long time. Effective ribozyme-mediated therapy also demands careful in vitro analysis of a ribozyme’s ability to efficiently and specifically distinguish between mutant and wild type RNAs. Acute Myeloid Leukemias: Acute Myeloid Leukemias are associated with a gene, AML1/MTG8, made by bringing together (translocation) two normal genes on different chromosomes and fusing them. Hammerhead ribozymes specifically targeted to split the RNA product of the AML1/MTG8 fusion gene and preventing it from acting. Connective Tissue Disorders: Ribozymes can inactivate the target RNA without relying on the host cell’s machinery and they have the capacity to cleave more than one copy of the target RNA by dissociating from the cleavage products and binding to another target molecule. Some dominant genetic disorders may also benefit from this approach. This is the case for some connective tissue disorders such as osteogenesis imperfecta, Marfan syndrome and the craniosynostotic syndromes 25. The effects of the relocation of the wild type termini on the folding of a cis-cleaving RNA Rz 1 that was modified from the autolytic domains of hepatitis delta virus (HDV) RNA were investigated26. AIDS: Human immunodeficiency virus type 1 (HIV-1) is the primary etiologic agent for Aquired Immune Deficiency Syndrome (AIDS). HIV-1 is a lentivirus, a separate genus of the Retroviridae, which are complex Indian J.Pharm. Educ. 39(2) April - June 2005 RNA viruses that integrate into the genome of host cells and replicate intracellularly. Ribozymes are catalytic RNA molecules with enzyme-like cleavage properties that can be designed to target specific RNA sequences within the HIV-1 genome. In addition to the genomic RNA, several RNA intermediates, including splice variants, can be targeted by a single ribozyme. Ribozyme gene therapy for HIV-1 infection is a therapeutic approach that offers several potential advantages over conventional therapies in that it can potentially impact on both viral load and restoration of the immune system. Ribozyme gene therapy may be used as an adjunct to chemotherapeutic drugs, effecting viral suppression, and facilitating immune restoration without problems of patient compliance. Currently, an anti-HIV-1 ribozyme is being tested in two separate Phase I clinical trials 27. Gene Shears Pvt. Ltd is developing hammerhead ribozyme technology for therapy against HIV infection, targeting either the tat gene or the RNA packaging sequence (Psi) of HIV. These ribozymes have been expressed from constructs that were introduced into hematopoietic cells in culture, thereby protecting the cells against viral infection. Two phase I clinical trials are underway to test the safety and feasibility of the approach with the anti-tat ribozyme in human subjects 28. Huntington Disease and Myotonic Dystrophy: Trinucleotide Repeat Expansions (TREs) are a recently described class of mutations characterized by a change in the size of the genomic fragment due to amplification of the repeated unit. A number of diseases have been attributed to TRE, including Huntington disease and myotonic dystrophy (DM), but attempts at gene therapy have yet to be proved successful. A potential therapeutic approach would be to repair the expanded repeat using the trans-splicing ability of group I intron ribozymes 29. CONCLUSION Since the discovery of ribozymes and self-splicing introns, it has been estimated that this biological property of RNA combined with other recombinant DNA technologies would become a tool to combat viral diseases and control oncogenes. These goals seem like a distinct possibility now. However, there is still a lot to be learned about the mobility of RNA inside the cells and the cellular factors that can impede ribozyme action in order to capitalize fully on the targeted RNA inactivation property of ribozymes. References 1. 2. 3. Rossi, J. J., Trends Biotechnol., 13, 1995, 301. Couture, L. A. and Stinchcomb, D. T., Trends Genet., 12, 1996, 510. Iyo, M., Kawasaki, H. and Taira, K., Curr. Opin. Mol. Ther., 4, 2002, 154. 95 4. Symons, R. H., Annu. Rev. Biochem., 61, 1992, 641. 5. Pyle, A. M., Science, 261, 1993, 709. 6. Dmitry, A., Samarsky, G. F., Bertrand, E., Singer, R. H., Cedergren, R. and Fournier, M. J., Biochemistry, 96, 1999, 6609. 7. Lewin, A. S. and Hauswirth, W. W., Trends Mol. Med., 7, 2001, 221. 8. Haseloff, J. and Gerlach, W., Nature, 334, 1988, 585. 9. Hampel, A. and Tritz, R., Biochemistry, 28, 1989, 4929. 10. Perriman, R., Delves, A. and Gerlach, W. L., Gene, 113, 1992, 157. 11. Czubayko, F., Riegel, A. N. and Wellstein, A., J. Biol. Chem., 269, 1994, 21358. 12. Koizumi, M., Hayase, Y., Iwai, S., Kamiya, H., Inoue, H. and Ohtsuka, E., Nucl. Acid. Res., 17, 1989, 7059. 13. Cech, T. R., Annu. Rev. Biochem., 59, 1990, 543. 14. Galloway-Salvo, J. L., Coetzee, T., and Belfort, M., J. Mol. Biol., 211, 1990, 537. 18. Phylactou, L. A., Darrah, C., and Wood, M. J. A., Nat. Genet., 18, 1998, 378. 19. Phylactou, L. A., Kilpatrick, M. W. and Wood, M. J., Hum Mol Genet., 7, 1998, 1649. 20. Macpherson, J. L., Ely, J. A., Sun, L. Q. and Symonds, G. P., Front Biosci., 1, 1999, 497. 21. Phylactou, L. A., Adv. Drug Deliv. Rev., 44, 2000, 97. 22. Welch, P. J., Barber, J. R. and Wong-Staal, F., Curr. Opin. Biotechnol., 9, 1998, 486. 23. Grassi, G. and Marini, J. C., Ann. Med., 28, 1996, 499. 24. Lai, Y. C., Lee, J. Y., Liu, H. J., Lin, J. Y. and Wu, H. N., Biochemistry, 9, 1996, 124. 25. Alama, A., Barbieri, F., Cagnoli, M. and Schettini, G., Pharmacol. Res., 36, 1997, 171. 26. Hauswirth, W. W., LaVail, M. M., Flannery, J. G. and Lewin, A. S., Clin. Chem. Lab. Med., 38, 2000, 147. 15. Sullenger, B. A. and Cech, T. R., Nature, 371, 1994, 619. 27. Sioud, M., Curr. Mol. Med., 1, 2001, 575. 28. deFeyter, R. and Li, P., Curr. Opin. Mol. Ther., 2, 2000, 332. 16. Jones, J. T., Lee, S. W. and Sullenger, B. A., Nat. Med., 2, 1996, 643. 29. Khan, A. U. and Lal, S. K., J. Biomed. Sci., 10, 2003, 457. 17. Sarver, N. and Cairns, S., Nat. Med., 2, 1996, 641. 96 30. Pennati, M… et al., Oncogene., 15, 2004, 386. Indian J.Pharm. Educ. 39(2) April - June 2005 Pharm. Chemistry Microwave Assisted Rapid Quantitative Analysis of Aspirin, Calcium Carbonate and Riboflavin Shrishailappa Badami, Natasha Joseph Chelapureth, Deepa S, Sandhya Deepa E, Elna Merilla Bose, Vijeesh Govindan and Suresh B Dept.of Pharmaceutical Chemistry, J.S.S. College of Pharmacy, Ootacamund 643 001 Received on 25.09.2004 Modified on 31.01.2005 Accepted on 05.02.2005 ABSTRACT In recent years microwave technology is being used in laboratories for organic synthesis. In order to utilize the technology in Pharmaceutical Analysis the microwave methods for the quantitative analysis of aspirin, calcium carbonate and riboflavin were developed. All the assays were carried out successfully in lesser durations and with similar percentage purity as compared to the conventional heating. The procedures developed can be used routinely for practicals in Pharmaceutical analysis laboratories. INTRODUCTION Ways to minimize the consumption of energy has received enormous attention in recent times. In the past few years, microwave heating has been found to be a convenient source of energy and economic by saving energy, fuel and electricity1. A very short response time and better yield of the products are the main advantages of microwave heating. It finds a large number of applications in industries and laboratories. Earlier studies carried out in our laboratories have shown the use of microwave technique in the synthesis of organic molecules, analysis of oils, degradation of natural products and qualitative analysis 2-4. In view of the advantages of the microwave technique, in the present work, we report quantitative analysis of aspirin, calcium carbonate and riboflavin under microwave irradiation. The time required for completion of reaction, purity, ease of work up, simplicity and overall safety of procedure were studied and compared with the conventional Pharmacopoeial procedures 5. MATERIALS AND METHODS Equipment and Chemicals Microwave oven (LG Health Ware System, MG-605 AP, 900 Watts, 230 V, 50 Hz), was used. All the chemicals used were of analytical grade. Assay of Aspirin The assay of aspirin was conducted as per Indian Pharmacopoeia 5. A mixture of aspirin (1.5 g), ethanol (95%, 15 ml) and 0.05 N NaOH (50 ml) was taken in a conical flask boiled gently for 10 min, cooled and titrated the excess of alkali with 0.5 N HCl using phenol red as indicator. The percentage purity of the sample was calculated. The assay was also carried out using the following microwave method. A mixture of aspirin (1.5 g), ethanol (95%, 15 ml) and 0.05 N NaOH (50 ml) was taken in a conical flask and covered with a funnel. It was placed in a domestic Indian J.Pharm. Educ. 39(2) April - June 2005 microwave oven and subjected to microwave irradiation. Several separate experiments were conducted at different intensities and for various durations. Each reaction mixture was cooled and titrated against 0.5 N HCl using phenol red as indicator. Based on the results obtained 350 W intensity and 2 min heating duration was fixed and the assay was repeated thrice under these conditions. The average percentage purity was noted. Assay of Aspirin in Aspirin - caffeine Tablets The assay of aspirin in aspirin - caffeine tablets was carried out as per Pharmacopoeial procedure 5. Aspirin caffeine powder equivalent to 0.7 g aspirin was taken in a RB flask and mixed with sodium citrate (2 g) and 20 ml water. The mixture was refluxed for 30 min, cooled and washed the condenser with 30 ml of warm distilled water and titrated with 0.5 N NaOH using phenolphthalein as indicator. The percentage purity of the sample was calculated. The assay was also carried out using the same aspirin - caffeine powder under microwave irradiation in a beaker covered with a petridish containing ice using the same quantities of reagents except using 250 ml of distilled water. The reactions were conducted at various microwave intensities and for different durations. The percentage purity in each case was calculated and compared with the conventional results. At 950 W and for 18 min microwave heating produced the same results as that of conventional. Under these conditions the assay was repeated thrice and the average percentage purity was noted. Assay of Calcium Carbonate The assay of calcium carbonate was carried out as per Indian Pharmacopoeia 5. Calcium carbonate (0.1 g) was taken and dissolved in 3 ml of dilute HCl and mixed with distilled water (10 ml), boiled gently for 10 min, cooled and 10 ml of MgSO4 and NH3-NH4Cl buffer (10 ml) were added. The volume was adjusted to 50 ml with distilled 97 water and titrated against 0.05M disodium EDTA using mordent black – II as indicator. The percentage purity was calculated. The assay was also carried out under microwave irradiation in a beaker covered with a petridish containing ice using the same quantities of reagents except using 50 ml of distilled water along with 3 ml of dilute HCl. The assay was carried out at various intensities and for different durations in separate experiments. Based on the results obtained 750 W intensity and 4 min heating was fixed. Using these conditions the experiment was repeated thrice and the average percentage purity was noted. Assay of Riboflavin The assay was also carried out in subdued light as per Indian Pharmacopoeia 5. To a weighed quantity of riboflavin (75 mg), distilled water (150 ml) and glacial acetic acid (2 ml) were added and heated on a water bath for 1 h with frequent agitation until riboflavin was dissolved. It was cooled and diluted with distilled water to 1000 ml. To 10 ml of this solution, 3.5 ml of 0.1 M sodium acetate was added and diluted with distilled water to 50 ml. The extinction of the resulting solution was measured at 444 nm. The content of riboflavin was calculated taking 323 as the E1%, 1 cm at the maximum at 444 nm. The assay was also carried out in subdued light under microwave irradiation. A weighed quantity of riboflavin (75 mg), distilled water (150 ml) and glacial acetic acid (2 ml) were taken in a 500 ml beaker and heated in a microwave oven. The solution was cooled and diluted with distilled water to 1000 ml. To 10 ml of this solution, 3.5 ml of 0.1 M sodium acetate was added and diluted with distilled water to 50 ml. The extinction of the resulting solution was measured at 444 nm. The content of riboflavin was calculated taking 323 as the E1%, 1 cm at the maximum at 444 nm. Several experiments were conducted at various intensities and for various durations. Based on the results, 100% intensity and 4 min duration was fixed. Using these conditions, the experiment was repeated thrice and the average percentage purity was noted. RESULTS AND DISCUSSION Assay of aspirin by the conventional procedure involving 10 min heating gave a percentage purity of 98.23. The assay under microwave heating at 350 W intensity for 2 min gave 99.63% purity. Assay of aspirin in aspirin - caffeine tablets by the conventional heating for 30 min gave 98.14% purity and by the microwave method at 950 W for 18 min showed 99.05% purity. In the assay of calcium carbonate, the conventional method involving 10 min heating showed 98.8% purity and the microwave method at 750 W for 4 min resulted in 99.39% purity. The percentage purity of riboflavin obtained by the conventional method of 1 h heating was found to be 99.60 and the same by the microwave method at 100% intensity for 4 min heating time was found to be 99.68. All these readings are an average of three readings. In conclusion, we have developed rapid quantitative estimation procedures for the assays of aspirin, calcium carbonate and riboflavin under microwave irradiation. The conventional kitchen microwave can be used without any modification in the laboratories. The other advantage of this technique is several students simultaneously can perform reactions in one microwave. Hence, the technique is found to be a fast, cheap, reliable and ecofriendly that can be used routinely in Pharmaceutical analysis laboratories. The technique is presently being practiced for B.Pharm practicals in our institution. Table 1: Duration and percentage purity of quantitative estimations by conventional and microwave methods Sl. No. 1 2 Experiment Assay of aspirin Assay of aspirin in aspirin-caffeine tablets 3 Assay of calcium carbonate 4 Assay of riboflavin *Average of three readings Duration by method, min Conventional Microwave 10 30 02 18 98.23 98.14 99.63 99.05 10 04 98.80 99.39 60 04 99.60 99.68 Acknowledgement The present work is a part of B. Pharm project work and the authors acknowledge His Holiness Jagadguru 98 % Purity by method* Conventional Microwave Sri Shivarathri Deshikendra Maha Swamigalawaru of Suttur Mutt, Mysore, for providing the facilities and support. Indian J.Pharm. Educ. 39(2) April - June 2005 References 1. 2. 3. Suresh B., Determination of Saponification value using microwave irradiation, Indian Drugs, 39, 2002, 451-452. Sharma S.V., Rama Sharma G.V.S. and Suresh B., More Chemistry: An eco-friendly technology, Indian Journal of Pharmaceutical Sciences, 64, 2002, 337344. 4. Sharma S.V., Badami S., Venkateshwarlu L. and Suresh B., Microwave technology in Pharmaceutical chemistry practical: synthesis of organic drugs, Indian drugs, 40, 2003, 450-454. Badami S., Manohara Reddy S.A., Sharma S.V., and Badami S…. et al., Use of Microwave Technique in Pharmaceutical Organic Chemistry Practical, Indian Journal of Pharmaceutical Education, 37, 2003, 199203. 5. Indian Pharmacopoeia, Vol. 1, 4th Ed., Delhi:Controller of Publications, Govt. of India, 1996. Indian J.Pharm. Educ. 39(2) April - June 2005 99 Pharm. Education Institutional Excellence – An Approach to Contend in Global World A. M. Godbole and S. A. Sreenivas Department of Pharmaceutics, K.L.E.S’s College of Pharmacy, Hubli 580 031 Received on 28.10.2004 Modified on 06.01.2005 Accepted on 02.02.2005 A. M. Godbole S. A. Sreenivas ABSTRACT Education must undergo a paradigm shift in old norms and beliefs must be challenged. Colleges must learn to work with fewer resources. Education professionals must help students develop the skills they need to compete in the global world. Quality is a single most important issue in education which can bring a revolutionary change. The knowledge needed to improve our education system already exists within the education community. The major difficulty educational professional’s face today is their inability to deal with the ‘system failures’, which are preventing them, from developing new educational processes that will improve the quality of education. Every institution must have a strong desire, hunger to achieve more and more. In the present scenario of globalization which has even entered the field of education, the words like Reform or Perish and Change is the key word. The graduates coming out must be complete individuals with dynamism, good ability, problem solving skills, hard working graduates. To have a good product, pharmaceutical institution must gear up by adapting a systematic work plan and its effective execution. One can bring in a systematic transformation in style of working of an institution. Excellence and its achievements is not one man’s job but is purely work of a strong force of tough, determined individuals and the force must be headed by an able, dynamic, professional and above all a visionary. INTRODUCTION Pharmaceutical education in India is now a mass system - it has increased in size and heterogeneity. As a means of raising productivity and making the system focus upon outputs, pharmaceutical organizations have fostered diversification, choice, and competition. In a mass system, more graduates in particular areas of knowledge are produced: in other words, a competitive market for graduates is created. The process of valuing a graduate in the employment market is fraught with difficulties. Employers in the graduate market have little more to make their decision upon than the reputation of the degree. While they may have some information about the technical competence of a graduate in a field-specific area, they do not have information about employment-related skills or about the attainments of individual graduates in areas related to employment. To produce quality graduates by an organization/ institution needs to undergo whole process through quality. Quality in education can be incorporated by taking measures in all the corners, right from student admission to examination results. Nowadays pharmaceutical institutions are moving towards Accreditation and ISO certification for giving quality education and distinguish from the other institutions. Overall in India, there are only thirteen NBA accredited colleges and Karnataka has a good contribution of five colleges. One can blindly say that these accredited colleges give quality education but only to an extent. Hence now all the institutions who have been accredited are moving towards ISO certification. Institutions now well understand how to maintain 100 and develop their market position under such circumstances. The principal means of operation is to influence demand by providing subsidies to students— that is, to provide more services, better teaching, better research facilities, better libraries/on-line resources and the like for each rupee that a student spends at that institution. Vision and mission plays an important role in modifying the institution. Vision and Mission The organization’s vision is a statement that describes what the organization wishes to be in the future – an expression of the organization’s aspirations, the touch stone against which all actions, or proposed actions, can be judged, and is long-term. The mission is a statement of what the organization wants to achieve. The typical content is: • The role or contribution of the organization • The definition of the institution • • Specific, distinctive competencies Indications of future direction Achievement of quality and excellence Before embarking on this journey, one must have clear motives and the level of commitment that is present within an organization, particularly at the senior management level. There are two basic approaches to quality management implementation: · The “blitz” approach, where the whole organization is exposed very rapidly to the concepts and education started. This can lead to many problems Indian J.Pharm. Educ. 39(2) April - June 2005 associated with not knowing what to do next (or first), leading to an detrimental situation that is neither the implementation of quality nor achieving best to the organization. · The slow, planned purposeful approach that causes a gradual change to take place, so that “organization” becomes “the realization of quality and excellence” in a near seamless transition. An important first stage is for the organization’s leaders to be role models of a culture of quality and excellence, so that these ideas permeate the organization with support from the top. The three basic principles will never change and are very important: 1. Focus on the customer (Student) The customer should be mainly concentrated in the institutions, without which nothing can be achieved and if at all achieved, will go waste. What are graduate qualities/attributes/capabilities/ skills? Graduates should be enterprising and employable and should exhibit skills that global capital recognizes. They must have the attributes of worker flexibility (the ability to work as an individual or in teams based situations and hold attitudes of self responsibility towards up-skilling and re-skilling); have personal and transferable skills (highly developed communication skills and problem solving, be computer literate). In addition, workers should possess international perspectives so that they are able to understand the cultural forces that interact in their globalized work-place. While there are elements of this employability agenda in any set of abilities of graduates this paper takes the view that a university graduate should develop abilities that go beyond those related to employability. Indeed, the mix of skills, attributes, capabilities and qualities of a graduate are shaped by a complex balance of stakeholder interests. Inevitably, the value that is attached to such skills, attributes, capabilities or qualities depends on the interests of each stakeholder, and, at a system level, such interests may be represented by peak bodies who talk generally about the quality of graduates. There are wide-ranging differences in the ways that universities employ the notion of graduate qualities or skills. A major difference is the scope of the graduate qualities or skills and their public specification. Some universities prefer to limit their attention to employmentrelated skills and place lesser importance upon social and cultural areas such as ethical professional behavior, social responsibility and cultural plurality and sensitivity. Further, in some cases, the specification of the quality is limited to the cognitive (or other) skill, without any attention to the context of application of the skill. In such Indian J.Pharm. Educ. 39(2) April - June 2005 cases, it is left open whether the skill may apply to the context of personal action, behavior in a professional group, or actions as a socially responsible citizen. Whatever the level of specification, there are two key characteristics which set the parameters for the degree of practical commitment that an institution has in applying their concept of graduate qualities. These are: · the extent to which curriculum design for courses is directed towards achieving a particular set of qualities, and · the extent to which formal assessment and reporting (both formative and summative) are shaped by the qualities. 2. Measures of institutional commitment to graduate qualities The two key characteristics mentioned at the end of the previous section, curriculum intention and assessment and reporting, can work together to provide a signal to the market about the extent to which a university is prepared to assure the market (and institutional stakeholders) of its commitment to delivering graduates who have the particular qualities or attributes that the institution claims. In attempting to provide such assurances, universities may take a variety of positions. For the purpose of describing of a continuum of positions, a strong position is where: · the course and the teaching is designed to develop graduate qualities, and · the summative assessment tasks and techniques have been changed to assess the level of development of each quality in students and this is reported upon by the institution. A weak position is where there is neither conscious attempt to design or teach for graduate qualities nor any formal student assessment for such qualities. There is, however, a further dimension to add to the above positions. A strong position is where the course of study is designed to develop graduate qualities, and, as a part of the delivery of the course, students are encouraged to compile a portfolio of experiences or work completed. Such a folio would provide evidence of their attainments in either the complete set of qualities expected in a graduate or in those areas/qualities thought to be employment related. Institutions might further support this activity by providing a statement of their intentions that courses develop a set of graduate qualities and supply course outlines that demonstrate those intentions. 3. All staff members are committed to quality and excellence Staff members should be totally dedicated to the 101 improvement of the institution and students. The role of faculty carries lot of importance in building a quality institution. Faculty members must have an unending urge to excel by constant upgradation of their knowledge. They must be provided with all necessary assistance to carryout research and publications. The faculty members should have an unending courage for learning and selfrenewing. Self-renewing faculty will contribute more for the development of the institution by their following efforts. There are at least ten basic qualities shared by self-renewing teachers who seek to be their best in all seasons of their lives for the development. 1. They are value-driven Self-renewing faculties are committed to values and purpose. They know what they prefer. Their primary anchors are within themselves. For them, renewal is not mere responsiveness to change; it is the repeated revival of the central concerns of their lives within the changing contexts in which they find themselves. Something is always at stake, something matters, and time gets organized around those critical priorities. They are determined to make a difference. 2. They are connected to the world around them Self-renewing faculty stay connected to the world around them. They are not loners. They seek out friends who can and will talk about whatever needs to be talked about the whole of life experience, up and down and all around. They listen and empathize with life everywhere. They care and communicate. They stay in contact with their children and/or parents, students and colleagues, and take initiative in sustaining relationships. They may not be joiners, but they feel that the world is there for them to enjoy, to grab on to, and to learn from. They network information, contacts, and resources. They support causes and take stands. 3. They require solitude and quiet Self-renewing faculty requires times of solitude and quiet. They know how to refill their cups before they get emptied. They plan time for introspection as well as for interaction and decision-making. They have private lives that they nurture and love. They have regularly scheduled times when they withdraw from routines to spend time alone. They retreat to some “secret garden” where renewal is predictable, simple, spontaneous, and wonderful. In solitude, they look, listen, meditate, and nurture themselves. They honor their inner life and outer boundaries. sustain the self-renewal process. Renewal must be built into the ordinary, chaotic, ongoing rhythms of our lifestyles and work-styles. Self-renewing faculty pace themselves, they schedule episodic breaks from their routine time, such as travel, holidays, vacations, retreats, seminars, and ruthless situation. They are not trying to sustain optimal performance at everything they do; rather, they seek to be fully present and available for all the occasions of their life course. They are more interested in quality time than in busy schedules, more concerned with effective lives than with efficient actions, more committed to integrity and style than to short-term results and applause. 5. They learn from downtime Self-renewing faculty learns from their disappointments, necessary losses, and down times. Like the lives of most people, their lives are sometimes full of funk and disorientation. They do not live lives without stress, failures, mistakes, loss and tragedy. Their lives are not sweet or perfect. They know that they have unresolved conflicts, limited perspectives, and impulses that sometimes overpower them. They do not deny the dilemmas of their lives. They accept the loose ends and unfinished business of their lives as part of their own future agenda. CONCLUSION In this paper we have tried to give brief details with which the institution can march towards excellence. As the trends are changing, the graduates who are the outcome of the institution should be built up with all the character to compete in the global market and can protract the challenge in the employment market. By implementing quality in the education, the system can be transformed to meet the on going global challenges. References 1. 2. 3. 4. http://www.espa-online.org/ Madhavan, M., TQM in Educational Institutions, Indian. J. of Tech. Edu., 20(3), 1997, 24-27. 5. Jorgensen, N. E. and Weil, T.P., Regulating Managed Care Plans, Managed Care Quarterly, 6 (3), 1998, 716. 6. 7. http://depts.washington.edu/pha/ National Association of Boards of Pharmacy Home Page. Available from: http://www.nabp.net.Accessed April 14, 2000. Kale, Shantanu, Pharmacy Education: Current Problems and Suggested Solutions, Indian. J. Pharm. Educ., 38(3) 2004, 154-160. 4. They pace themselves Our current practice for renewal is to indulge in rigorous work schedules throughout each week, punctuated by “time-off” on weekends and vacations. In a chaotic world, occasional breaks are not enough to 102 Shukla, Ravi N, A Quality Journey, Indian. J. of Tech. Edu., 25(1), 2002, 66-68. http://www.ijpe.org/oct2002/Articleo4page01.html 8. Indian J.Pharm. Educ. 39(2) April - June 2005 Pharm. Chemistry CoMFA-A 3D QSAR Approach And Its Applications Sanmati K. Jain SLT Institute of Pharm. Sciences, Guru Ghasidas University, Bilaspur-495009 Received on 29.10.2004 Accepted on 29.12.2004 ABSTRACT Comparative Molecular Field Analysis (CoMFA) is the most frequently used receptor-independent (RI) 3D-QSAR approach, reflecting a novel, conceptually satisfying scientific approach. In this method a relationship is established between the biological activities of a set of compounds and their steric and electrostatic properties. CoMFA has shown its practical value in drug design. INTRODUCTION Comparative Molecular Field Analysis (CoMFA) is a three-dimensional quantitative structure activity relationship (3D-QSAR) approach, introduced in 1988 by Cramer1,2. In 1979, Cramer and Milne made a first attempt to compare molecules by aligning them in space and by mapping their molecular fields to a 3D grid 3. CoMFA approach was an application of the dynamic lattice oriented molecular modeling system (DYLOMMS), as it was called till 1987. A real advance resulted in 1987, the method was still named DYLOMMS but now it used grids including several thousands of points, partial least squares (PLS) analysis and most important, a crossvalidation procedure to check the predictive ability of different models. In 1988, a key publication appeared2 and the method was called comparative molecular field analysis (CoMFA) from then and on. CoMFA is a receptor-independent (RI) 3D-QSAR approach, reflecting a novel, conceptually satisfying scientific approach reduced to practice as a well-written and versatile software package. In this method a relationship is established between the biological activities of a set of compounds and their steric and electronic properties 4. Steps of a CoMFA There are several important and critical steps in a CoMFA study. CoMFA describe 3D structure activity relationships in a quantitative manner. First, a group of compounds which have a common pharmacophore is selected to be included in the analysis. As a most important precondition, all molecules have to interact with the same kind of receptor (or enzyme, ion channel, transporter) in the same manner. Then three-dimensional structures of reasonable conformations must be generated from the 2D-structures. Several 2D/3D-conversion procedures are in use or have been described in literature, e.g.CONCORD 5-7 , AIMB8 , WIZARD & COBRA 9-12 . Alternatively, 3D- structures derived from crystallographic Indian J.Pharm. Educ. 39(2) April - June 2005 analysis or 2D- NMR studies may be used. The energyminimized structures are stored in a database and fitted to each other according to their chemical similarity by using a pharmacophore hypothesis and postulating orientation rules. In the next step, a certain subgroup of molecules is selected which constitutes a training set to derive the CoMFA model. The residual molecules are considered to be a test set which independently proves the validity of the derived model(s). A sufficiently large box is positioned around the molecules and a grid distance is defined. Different atomic probes, e.g., a carbon atom, a positively or negatively charged atom, a hydrogen bond donor or acceptor, or a lipophilic probe, are used to calculate field values in each grid point, i.e., the energy values which the probe would experience in the corresponding position of the regular 3D lattice. These ‘fields’ correspond to tables, most often including several thousands of columns, which must be correlated with the binding affinities or with other biological activity values. PLS analysis is the most appropriate method for this purpose. The result of the analysis corresponds to a regression equation with thousands of coefficients. Most often it is presented as a set of contour maps. These contour maps show favorable and unfavorable regions for electropositive or electronegative substituents in certain positions. Predictions for the test set (compounds not included in the analysis) and for other compounds can be made, either by a qualitative inspection of these contour maps or, in a quantitative manner, by calculating the fields of these molecules and by inserting the grid values into the PLS model. Molecular Alignment The molecular alignment, i.e. the selection and relative orientation of a certain 3D- structures out of several conformers of each molecule, is the most important determinant in a CoMFA study. A field fit procedure has been proposed to improve the alignment, 103 the objective of the field is to minimize the residual mean square differences between a fixed template field (consisting of a steric and electrostatic field) and the fields of the molecules to be aligned. It is claimed that most often better results are obtained by using this field fit, after a first, preliminary alignment of molecules. Rational methods for the alignment of congeneric molecules are e.g. the active analog approach and the distance geometry method13-15. In the active analog approach, large numbers of different conformations of the molecules are superimposed; often only a few conformations are allowed for all molecules, which lead to a restricted conformational space for their common pharmacophore. Distance geometry as the name implies, approaches geometric problems by focusing on the distances between points, rather than on coordinates or angles. In 3D-QSAR applications, the points are atoms, and the geometric problems can include conformational analysis, molecular alignment and ligand- receptor binding. Several other computer assisted or computersautomated procedures have been developed for the alignment of molecules. ALADDIN16 calculates the location of points, which may be considered for the superposition of the molecules for all low-energy conformers of a series of compounds. Such points are, e.g. atoms, ring centers, and projections from the molecule to hydrogen bond donor, acceptor, and charged groups at the binding site. The molecule with the smallest number of possible conformations forms the template. Disco1 7 uses a clique–detection method to find superposition of the molecules that contain at least one conformation of each compound in the user–defined three-dimensional arrangement of site points. The program CATALYST18 claims to use a corresponding strategy to derive 3Dpharmacophore from sets of active molecules and to search 3D-databases for hits that are ordered according to the quality of fit of the molecules to the hypothetical pharmacophore. Grid Size Once the molecules are aligned a grid or lattice is established which surrounds the set of analogs in potential receptor space. Current CoMFA studies seldom use grid resolution less then 1 Ao and, most often, 2 Ao. The choice of grid resolution represents a compromise between computational practicality and detailing of the fields. If the grid resolution is too small, the number of field–points (cells) becomes too large to perform a timely 104 analysis. Moreover spatial information on field preference can be lost, through a ‘smearing out’ effect, if the cells become too small. The grid resolution in the 1 to 2 Ao range corresponds to, at best, differentiating single carbon-carbon (1.54 Ao) from one another. Probes Any chemical unit can be used as a field probe in a CoMFA analysis. Also, the number of field probes used to construct a 3D-QSAR is not limited. In practice, three (default) probes are usually employed: a steric probe, a positive–charge probe, and a negative–probe. It is assumed that the selected set of field probes will at the least identify the major receptor field characteristics in biological activity for the training set of ligands. CoMFA Interaction Energy The fields that a certain probe atom would experience at every grid point are calculated for each molecule, leading to thousands of columns in the X-block. For steric field a (a/r12- b/r6) Lennard -Jones potential is calculated, the electrostatic field is 1/r Coulomb potential. The commercial version of CoMFA uses a (Îr) -1 distance dependant coulomb potential to evaluate electrostatic fields, where r is the probe-ligand atom distance and Î is the molecular dielectric. In the large majority of applications Î is set to the default value of unity. Large positive energy values, i.e. grid points inside the molecules are set constant at certain cut-off valued to avoid unreasonably large energy values. The default value of 30 kcal/mole is used as the maximum electrostatic and steric energy cutoff. Normally, the steric and electrostatic fields are kept separate for ease of interpretation of the results. Grid points without variance (e.g. in the corners of the box, far away from the van der Waals spheres of the molecules) are eliminated before the analysis is performed. Other fields than those implemented in the CoMFA program have been proposed for 3D-QSAR analyses, e.g., different interaction fields calculated by the program GRID19,20 or hydrophobic fields derived from HINT21-23. In addition, any other parameters, e.g. physico-chemical properties like log P or quantum-chemical indices, may be added to the X-block, if they are properly weighted. Partial Least Squares (PLS) and Cross-Validation in CoMFA The last step in a CoMFA is a partial least square analysis to determine the minimal set of grid points which Indian J.Pharm. Educ. 39(2) April - June 2005 is necessary to explain the biological activities of the compounds. Partial least–squares is an iterative procedure that applies two criteria to produce its solution. First, to extract a new component, the criterion is to maximize the degree of commonality between all of the structural parameter columns (independent variable) collectively and the experimental data (dependent variable). Second, in the evaluation phase of a PLS iteration, the criterion for acceptance of the principal component just generated is an improvement in the ability to predict, not to reproduce, the dependent variable. The technique used in PLS to assess the predictive ability of a QSAR is cross-validation24. Cross-validation is based on the idea that the best way to assess predictive performance is to predict. When cross-validating, one pretends that one or more of the unknown experimental value is, in fact, unknown. The analysis being crossvalidated is repeated, excluding the temporarily ‘unknown’ compounds and then using the resulting equation to predict the experimental measurement of the omitted compound(s). The cross-validation cycle is repeated until each compound has been excluded and predicted exactly once. The results of cross-validation are the sum of the squared prediction errors, sometimes called the predicted residual sum of squares (PRESS). For evaluation of the overall analysis, the PRESS is commonly expressed as a cross–validated correlation coefficient r2, or xv - r2, value. In CoMFA two r2 values are encountered in addition to the xv-r2. The second r2 is the conventional, and is a measure of how well a particular model reproduces or fits the input data. It is calculated in the same way as xv-r2, except that PRESS is replaced by the sum of the squares of differences between the least-squares fit and the experimental observations. In PLS both values are obtained the xv-r2 in the cross-validation step and conventional r2 in describing the final best-fit model. The third r2 value, the predictive r2, arises after a QSAR has been used to predict the target property of structures not included in the training set. r2cv = 1- PRESS / (Y - Ymean )2 Where, PRESS = S (Y - Ypred)2 Predictive r2 r2pred = (SD-PRESS) / SD Where, SD = sum of squared deviations between biological activities of the test set and mean activity of the training set molecules. Indian J.Pharm. Educ. 39(2) April - June 2005 PRESS = sum of squared deviations between predicted and actual activity values for every molecule in the test set. The PLS variant, generated optimal linear PLS estimations (GOLPE) 25,26 seems to be better suited than ordinary PLS analysis, because it eliminates variables not contributing to prediction in a stepwise procedure. Some recent applications in CoMFA studies confirm that the predictive power of the CoMFA model increases after reduction of the number of variables according to the GOLPE procedure. The risk of chance correlation seems to be low in CoMFA studies if arbitrary orientations of the molecules are chosen instead of a reasonable alignment or if series of random numbers are correlated with biological activities 27. CoMFA RESULTS Most often the results of a CoMFA study are presented in graphical form. Typically, there will be two contour levels displayed for each type of CoMFA field, highlighting the regions of greatest association; the most positive and the most negative. These contour maps are helpful in suggesting new compounds likely to have higher property values. The CoMFA QSAR equation can also be used to predict property values, providing a vehicle for ranking potential compounds for synthesis. Difference maps are proposed as tools to analyze and identify areas of interest with respect to activity and selectivity, if two different types of biological activities are compared. CoMFA offer many different options resulting from slightly different alignments of the molecules or certain side chains, different positions or sizes of the grid boxes, the use of different fields and additional variables, different values for the cut-off of large positive energy values, etc. This flexibility of the CoMFA method makes it a powerful tool to perform a QSAR study. Biological activities of new compounds can be predicted by transforming the PLS result into a multiple regression equation28,29. For a comparison of classical QSAR analyses with 3D-QSAR studies the PLS results have been presented in the form of multiple regression equations, including the PLS components as the independent variables. One can not expect reliable predictions of biological activity values for analogs having additional side chains or groups with significantly different electronic properties. The use of additional or other fields than the default steric and electronic fields 105 of the original CoMFA method, together with PLS analysis or GOLPE, is quite common as a valuable extension of the CoMFA program. APPLICATIONS OF CoMFA The first application of CoMFA was to a series of steroid molecules. It correlates the binding affinities of 21 steroids to human corticosteroid globulins (CBG) and testosterone binding globulins2, (TBG). There are many reports in the literature of successful application of CoMFA that have not only led to predictive models within an analogue series of biologically active molecules 30, but also to insightful information on the general requirements for the expression of the activity. CoMFA and related 3D–QSAR approaches have been applied to correlate various physico-chemical properties. 3D-QSAR studies that correlate s, inductive and resonance parameters of benzoic acids31 as well as pKa value of clonidine analogs32 show that a H+ field precisely describes such electronic parameters, e.g. s m, p of benzoic acids. Steric parameters of benzoic acids, like surface area and van der Waals volume can be described by a steric field alone, while Es values of acetic acid methyl esters need a combination of both steric and electrostatic fields. CoMFA fields were also proposed and used to derive new steric and electronic parameters for classical QSAR studies. The CoMFA methodology can also be used to describe non-linear lipophilicity activity relationship, e.g. the inhibitory activities of quaternary alkylbenzyl dimethyl ammonium compounds vs. Clostridium welchii33, other antibacterial and hemolytic activities, and toxic activities of alkanes in mice, only homologous series of compounds can be investigated34,35. CoMFA a ligand interaction based model deals with the quantitative description of ligand- protein interactions, like enzymes, e.g., angiotensin converting enzyme inhibition36, prostaglandin synthetase inhibition, renin inhibition 37, carbonic anhydrase inhibition 38 , interleukin 1-b converting enzyme (ICE) inhibition39 , arylalkylamine N-acetyl transferase (AANAT) inhibition40, selective COX-2 inhibition41, receptor binding, e.g., binding of a 1-adrenergic agonists, benzodiazepine receptor binding42-45, H2 receptor binding46, endothelin receptor antagonism47, adenosine A 2A receptor binding48, ion channels, e.g., hydantoin binding of neuronal voltage–sensitive channel 49 , calcium ion channel inhibition50 and other ligand –protein interactions, e.g., the binding of steroids to various carrier proteins51-53, 106 GABA-uptake inhibition, ligand binding to viral coat proteins54 etc. CoMFA also applied to correlate various other biological activities, e.g., response of tumor cells to estrogens 55, diuretic activities of sulfonamides in the isolated perfused tubulus of rabbit kidney, various biological activities of prostaglandin analogs56 and 3DQSAR of antihyperglycemic agents (2,4thiazolidinediones)57. LIMITATIONS However, despite the simplicity of the analysis and the good correlation obtained in these studies, a ligandinteractions based model like the CoMFA method should not be used to model non-linear effects arising from transport and distribution, no reasonable results can be expected for sets of compounds which are no homologous series. References 1. Cramer, R.D., Patterson, D.E and Bunce, J.D., J Am Chem Soc, 110, 1988, 5959. 2. Clark, M…. et al., Tetrahedron Comput Methodology, 3, 1990, 47. 3. Cramer III, R.D. and Milne, M., Abstracts of Papers, Am Chem. Soc., April 1979, Computer Chemistry Section, no. 44. 4. Charifson, P.S. (ed), Practical application of computer-aided drug design, New York: Marcel Dekker, 1997, 109. 5. Pearlman, R.S., Chem. Design Automation News, 2(1), 1987, 1. 6. Rusinko, A…. et al., CONCORD, Tripos Associates Inc., St. Louis, MO, USA. 7. Kubinyi, H. (ed.), 3D-QSAR in drug design, theory, methods, and applications, Leiden: ESCOM Science Publishers, 1993. 8. Wipke, W.T. and Hahn, M.A., Tetrahedron Comp. Methodology, 1, 1988, 141. 9. Dolata, D.P., Leach, A.R. and Prout, K., J Comput Aided Mol Des, 1, 1987, 73. 10. Leach, A.R., Prout, K. and Dolata, D.P., J Comput Aided Mol Des, 2, 1988, 107. 11. Leach, A.R., Prout, K. and Dolata, D.P., J Comput Chem, 11, 1990, 680. 12. Leach, A.R. and Prout, K., J Comput Chem, 11, 1990, 1193. Indian J.Pharm. Educ. 39(2) April - June 2005 13. Humblet, C. and Marshall, G.R., Drug Dev Res, 1, 1981, 409. 35. Kim, K.H., J Comput Aided Mol Des, 7, 1993, 71-82. 14. Mayer, D., Naylor, C.B., Motoc, I. and Marshall, G.R., J Comput Aided Mol Des, 1, 1987, 3. 37. Klebe, G. and Abraham, U., J Med Chem, 36, 1993, 70. 15. Dammkoehler, R.A…. et al., J Comput Aided Mol Des, 3, 1989, 3. 38. Baldwin, J.J…. et al., J Med Chem, 32, 1989, 2510. 16. Van Drie, J.H., Weininger, D. and Martin, Y.C., J Comput Aided Mol Des, 3, 1989, 225. 17. Martin, Y.C… et al., J Comput Aided Mol Des, 7, 1993, 83. 18. CATALST, Bio CAD Corporation, Mountain View, CA, USA. 19. Goodford, P. J., J Med Chem, 28, 1985, 849. 20. GRID Program, V7, Molecular Discovery Ltd. West Way House, Elms Parade, Oxford, England. 21. Wireko, F.C., Kellog, G.E. and Abraham, D.J., J Med Chem, 34, 1991, 758. 22. Kellog, G.E., Semus, S.F. and Abraham, D.J., J Comput Aided Mol Des, 5, 1991, 545. 23. Kellog, G.E. and Abraham, D.J., J Mol Graphics, 10, 1992, 212. 24. Cramer, R.D., Bunce, J.D. and Pattersonm D.E., Quant Struct Act Relat, 7, 1988, 18. 25. Baroni, M…. et al., J Chemometrics, 6, 1992, 347. 26. Baroni, M…. et al., Quant Struct Act Relat, 12, 1993, 9. 27. Clark, M. and Cramer, R.D., Quant Struct Act Relat, 12, 1993, 137. 36. Marshall, G.R., Eur J Pharmacol, 183, 1990, 15. 39. Kulkarni, S.S. and Kulkarni, V.M., J Med Chem, 42, 1999, 373. 40. Chavatte, P… et al., Quant Struct Act Relat, 20, 2002, 414. 41. Marot, C., Chavatte, P. and Lesieur, D., Quant Struct Act Relat, 19 (2), 2000, 127-34. 42. Allen, M.S…. et al., J Med Chem, 33, 1990, 2343. 43. Diaz-Arauzo, H., Koehler, K.F., Hagen, T.J. and Cook, J.M., Life Sci, 49, 1991, 207. 44. Allen, M.S…. et al, J Med Chem, 35, 1992, 4001. 45. Greco, G., Novellino, E., Silipo, C. and Vittoria, A., Quant Struct Act Relat, 11, 1992, 461. 46. Dove, S. and Buschauer, A., Quant Struct Act Relat, 18, 1999, 329. 47. Chen, Q… et al., Quant Struct Act Relat, 18, 1999, 124. 48. Dotychinova, I., Valkova, I. and Natcheva, R., Quant Struct Act Relat, 20 (2), 2001, 124. 49. Brown, M.L….. et al, J Med Chem, 42, 1999, 1537. 50. Schleifer, K.J. and Tot, E., Quant Struct Act Relat, 21 (3), 2002, 239. 51. Norinder, U., J Comput Aided Mol Des, 5, 1991, 419. 28. Norden, B., Edlund, U., Johnels, D. and Wold, S., Quant Struct Act Relat, 2, 1983, 73. 52. Opera, T.I., Ciubotariu, D., Sulea, T.I. and Simon, Z., Quant Struct Act Relat, 12, 1993, 21. 29. Norinder, U., J Comput Aided Mol Des, 4, 1990, 381. 53. Loughney, D.A. and Schwender, C.F., J Comput Aided Mol Des, 6, 1992, 569. 30. Thibuat, U., ‘Application of CoMFA and related 3DQSAR approaches’ in 3D-QSAR in drug design; theory, methods and applications (Kubinyi, H., ed.), Leiden: ESCOM Science, 1993, 661. 31. Kim, K.H. and Martin, Y.C., J Org Chem, 56, 1991, 2723. 32. Kim, K.H. and Martin, Y.C., J Med Chem, 34, 1991, 2056. 33. Kim, K.H., Med Chem Res, 2, 1992, 22. 54. Diana, G.D…. et al, J Med Chem, 35, 1992, 1002. 55. Wiese, T.E., Palomino, E., Horwitz, J.P. and Brooks, S.C., Abstracts of Papers, Am Chem Soc, April 1991, Medicinal Chemistry Section, no. 150. 56. Koehler, K.F…. et al, Abstracts of Papers, Am Chem Soc, August 1990, Medicinal Chemistry Section, no. 75. 57. Kulkarni, S.K., Gediya, L.K. and Kulkarni, V.M., Bioorg Med Chem, 7, 1999, 1475. 34. Kim, K.H., Quant Struct Act Relat, 11, 1992, 309. Indian J.Pharm. Educ. 39(2) April - June 2005 107 Pharm. Chemistry Spectrometric Method for Determination of Carbocysteine P. N. Sanjay Pai, Gopalkrishna Rao, B. Balakrishna, Hamid Khan and K. Pasha Department of Quality Assurance, Al-Ameen College of Pharmacy, Bangalore 560 027 Received on 17.8.2004 Modified on 28.1.2005 Accepted on 24.3.2005 ABSTRACT A simple, colorimetric method is developed for the estimation of carbocysteine. The method is based on the chemical reaction of primary amino group present in carbocysteine with carbon disulphide to form dithiocarbamic acid, which on further reaction with cupric chloride forms a colored copper chelate. The yellow chromophore has absorption maxima of 413 nm and obeys Beer’s law in the concentration range of 100-800 µg/10ml. Results of the analysis were statistically validated by recovery studies. The proposed method was found to be suitable for routine determination of carbocysteine as active pharmaceutical ingredient. Chemically carbocysteine is S-carboxymethyl Lcysteine. Carbocysteine has a significant importance as a potent expectorant and is used as mucolytic agent1. Literature survey reveals that the drug is determined mainly by HPLC2-5 methods. The main objective of the present study was to develop a sensitive and selective colorimetric method for routine estimation of carbocysteine by exploiting its amino group using dithiocarbamic acid method 6 . A Shimadzu UV/Vis Spectrophotometer (UV 1601) with 1 cm matched quartz cell was used. A standard solution of carbocysteine was prepared by dissolving 100 mg of carbocysteine in 10 ml of 10%w/ v sodium hydroxide. The volume was made up to 100 ml with dilute sodium hydroxide in a 100 ml volumetric flask to get a solution of strength 1 mg/ml. A 10% v/v aqueous acetic acid solution was prepared by diluting 10 ml of glacial acetic acid to 100 ml with distilled water. Carbon disulphide-pyridine- isopropyl alcohol reagent (CPI reagent) was prepared by mixing 35 ml of carbon disulphide, 25 ml of pyridine and 65 ml of isopropyl alcohol in accurate quantities. Cupric chloride solution was prepared by dissolving 0.12 g of cupric chloride in 250 ml of water and further diluted to 500 ml with pyridine. To 1 ml of the standard carbocysteine solution (1 mg/ml) taken in a separating funnel, 4 ml of CPI reagent and 2 ml of cupric chloride reagent were added. The mixture was then allowed to stand for 10 min, and then vigorously agitated. Further 3 ml of aqueous acetic acid solution and 3 ml of benzene were added. The mixture was agitated for 5 more min and the two liquid phases were allowed to separate. The upper organic layer was collected in a 10 ml volumetric flask, the volume made up with isopropyl alcohol solvent and allowed to stand for 20 min for complete development of colour. The solution was scanned in the wavelength region of 400-760 nm 108 against reagent blank. The absorption maxima of the yellow chromogen was found to be 413 nm. The method was validated for fixing optimum concentration and volume required for reagents to show maximum absorbance, stability of color and order of mixing. The colour was stable up to 2 hours. The standard curve was then plotted for linearity (concentration vs absorbance) and was found to be in the range of 100-800 µg/10ml. The molar absorptivity was determined to be 3.27×104 l. mol-1cm-1 and Sandell’s sensitivity 10.186 x 10-2 µg/cm20.001 absorption units. A regression equation (y=a+bx) was obtained by linear least squares treatment of the results, established slope(b) of 0.009816 and intercept(a) 0.0001, with relative standard deviation of 0.2308191 and coefficient of variation 0.05327. Percentage range of error was calculated as 0.23%. The accuracy and reliability of the method was proved through recovery studies. The method was extended for determination of carbocysteine in bulk drug samples obtained from three different manufacturers. A solution of 1 mg/ ml of the sample carbocysteine was prepared. The absorbance values obtained for the sample solution were correlated with standard calibration curve to obtain the concentration. The recovery studies were carried out at three levels by adding 0.1, 0.2 and 0.3 ml of standard solutions of carbocysteine to 0.2 ml each of previously analyzed samples in three 10 ml volumetric flasks. The mixtures were analysed by the proposed method. The results are presented in Table 1. The proposed colorimetric method is based on the principle of chemical reaction of primary amines in carbocysteine with carbon disulphide to form dithiocarbamic acid, which on further reaction with cupric chloride forms a yellow colored copper chelate, which is estimated colorimetrically. The scheme of this novel reaction is given in Figure 1. Indian J.Pharm. Educ. 39(2) April - June 2005 Table 1 : Recovery Study Std. Carbocysteine Conc(mcg) Sample Carbocysteine (mcg) Recovery of standard (mg) % Recovery 200 200 Amount Of carbocysteine from the std. graph (mg)* 295 394 100 200 95 194 95.0 97.4 300 200 502 302 100.6 * Average of 3 readings Figure 1: Dithiocarbamic acid – carbocysteine - copper complex The proposed method was found to be sensitive, accurate, precise and reproducible and can be used for the routine determination of carbocysteine bulk drug. Acknowledgement The authors thank Astra Zeneca Pharmaceuticals Limited, Bangalore for providing Reference standard Carbocysteine and also bulk samples of Carbocysteine supplied from different sources. The research team acknowledges Prof. B. G. Shivananda, Principal, Al – Ameen College of Pharmacy for providing the facility to carry out the work. 3. Pentari, J. G., Efstathiou, C. E. and Koupparis, M. A., Kinetic determination of carbocysteine in syrup based on its reaction with 1-fluoro-2,4-dinitrobenzene monitored with a fluoride-selective electrode, Int. J. Pharm., 77(31), 1991, 41-46. 4. De-Schutter, J.A., Vander, W. G., Vanden, B. W. and Demoerloose, P., Determination of Scarboxymethylcysteine in serum by reversed phase ion pair liquid chromatography with column switching following pre-column derivatization with ophthalaldehyde, J. Chromatogr., 428(15), 1988, 301310. 5. Dubruc, C… et al., Determination of S-carboxymethylL-cysteine in plasma by high performance liquid chromatography with column switching following precolumn derivatization, J. Chromatogr., 417(5), 1987, 208-215. Siggia, S. and Hanna, J.G., Quantitative Organic Analysis, 30 th Ed., New York: InterScience Publication, 1979, 615. References 1. Parfitt K., Ed, Martindale – The complete drug reference, 32nd Ed., London: Pharmaceutical press, 1999, 1056. 2. Staffeldt. B., Brockmoller, J. and Roots, I., Determination of S-carboxymethyl-L-cysteine and some of its metabolites in urine and serum by high performance liquid chromatography using fluorescent pre-column labeling, J. Chromatogr. Biomed. Appl., 571(15), 1991, 133-147. Indian J.Pharm. Educ. 39(2) April - June 2005 6. 109 Ph.D Thesis Title Candidate Institute University Guide(s) : : : : : Awarded : Study of anti-ulcer activity of some herbal drugs Siddhraj Singh Sisodia B.N. College of Pharmacy, Udaipur (Rajasthan) 313 002 Mohanlal Sukhadia University, Udaipur 1. Dr. M. Bhatnagar, Prof., Cellular and Neurobiology Lab., M.L.S. University, Udaipur (Raj.) 2. Dr. C.P. Jain, Assistant Prof., Dept. of Pharmacy, M.L.S. University, Udaipur (Raj.) 15 th February 2005 Received & accepted on: 14.03.2005 Peptic ulcer disease is one of the common gastrointestinal disorder affecting millions of people, it kills few but troubles many. The etiology of gastric ulcer is not known in most cases, but it is generally accepted that it results from an imbalance between aggressive factors (Gastric HCl, Pepsin secretion, H. Pylori, Alcohol, NSAIDs, Malignancy etc.) and defensive factors (Gastric mucosal barrier, Endogenous prostaglandin’s, Secretin, Somatostatin, Epidermal growth factors, blood flow etc.). Many herbal drugs are being used as Ayurvedic preparations or in Indian traditional medicinal system for the management of peptic ulcer. Withania somnifera Dunal is commonly known as “Ashwagandha” which means it has strength and odour of horse. Asparagus racemosus Willd. is commonly known as “Shatavari”. Shatavari is used for sexual debility and infertility in both sexes. Aim of the present investigation was to compare that anti-secretory, anti-ulcer and antioxidant activity of Asparagus racemosus willd. and Withania somnifera Dunal root extract with standard drug Rantidine in various models of gastric ulcer in rats. Ulcer was induced by the indomethacin (NSAID’s) and swim (restraint) stress treatment. Adult albino rats (Wistar strain) of the either sex were used for the present study. Dried roots (Asparagus racemosus and Withania somnifera) were purified using absorption method. After purification, the roots were packed in high quality filter paper and the successive solvent extract (methanol) was prepared by continuous extraction method with the help of soxhlet extractor. After vacuoevaporation crude extract was suspended in 0.5% Carboxy Methyl Cellulose (CMC). Acute administration of NSAIDs like indomethacin and pyloric ligation produced severe gastric lesion in stomach of rats. In the present study, Idomethacin treatment and pylorus ligation of animals significantly 110 increased the ulcer index, volume of gastric content, free acidity and total acidity when compared with control untreated group. In our study, methanolic extract of both drugs Asparagus racemosus (100 mg/ kg/ day, bw, p.o.) and Withania somnifera (100 mg/ kg/ day, bw, p.o.) reduced the incidence of gastric ulcer, volume of gastric content, free acidity and total acidity significantly in indomethacin induced gastric ulcerative rats. Decreased ulcer index and gastric content are implicated with the gastroprotective effects of drugs. Significant reduction in free and total acidity is also implicated in the anti-ulcer effect of these drugs. Administration of 50% reduced combined dose of Asparagus racemosus (50 mg/ kg/ day, bw, p.o.) plus Withania somnifera (50 mg/ kg/ day, bw, p.o.) also produced significant reduction in ulcer index, volume of gastric content, free acidity and total acidity as compared to control untreated group but their effects on these parameters were less as compared to independent administration of Asparagus racemosus (100 mg/ kg/ day, bw, p.o.) and Withania somnifera (100 mg / kg/ day, bw, p.o.). In the present study, experimental group showed significant decrease in total carbohydrate (TC) and decrease in TC/ Total protein (TP) ratio. Administration of Asparagus racemosus, Withania somnifera and 50% mix dose of Asparagus racemosus and Withania somnifera showed significant increase in total carbohydrate (TC) and TC/ Total protein (TP) ratio of the gastric juice. However, they did not have any effect on total protein of the gastric juice. Administration of 30 mg/ kg/ day, bw, p.o. ranitidine for 15 days produced significant decrease in ulcer index, volume of gastric content, free acidity and total acidity it also significantly increased the total carbohydrate (TC), Total Protein (TP) and TC/TP ratio. In the present study, important antioxidant status of indomethacin treated, indomethacin plus Asparagus racemosus, indomethacin plus Withania somnifera, 50% mix dose of Asparagus racemosus and Indian J.Pharm. Educ. 39(2) April - June 2005 Withania somnifera, only Asparagus racemosus and only Withania somnifera were also observed. All the treatment schedules for both the drugs significantly increased the level of catalase and superoxide dismutase (SOD) in the stomach, liver, lungs and kidney. In our study a significant increase in the antioxidant activity of gastromucosal, liver homogenate, lungs and kidney homogenate was evident as there was significant decrease in lipid peroxidation. In indomethacin treated group the level of malondialdehyde (MDA) was significantly increased where as ascorbic acid content decreased significantly. Stress ulceration in the stomach is associated with clinical conditions like trauma, head injury, burns, shock, sepsis and neurological disorders and thus now regarded as a multifactorial phenomenon. In the present investigation water immersion stress was used to produce severe gastric ulceration and hemorrhagic spots. The ulcer index, volume of gastric content, free acidity and total acidity were significantly increased after swim stress regimen in the present study. The result of the present study demonstrate the anti-ulcer activity of both root extract of Asparagus racemosus and Withania somnifera against stress induced gastric ulcerative rats which was evident from a significant decrease in the ulcer index, volume of gastric content, free acidity and total acidity. An increase in gastric acid secretion and reduction of gastric mucus (gastric content) play a major role in the pathogenesis of stress induced gastric ulcers. Total carbohydrate (TC) and TC/ Total protein (TP) ratio was significantly increased after the administration of Indian J.Pharm. Educ. 39(2) April - June 2005 Asparagus racemosus and Withania somnifera in stress induced gastric ulcerative rats. Defensive mucin secretion was quantified in term of TC/TP ratio in the gastric juice. TC/TP ratio is taken as a reliable marker for mucin secretion. The TC/TP ratio of stress plus Withania somnifera is more as compared to stress plus Asparagus racemosus and stress plus Ranitidine. Study also showed increase in antioxidant defense enzymes wiz superoxide dismutase, catalase and ascorbic acid increased significantly while a significant decrease in lipid peroxidation was observed after A. raemosus and W. somnifera treatment in stress induced gastric ulcerative rats. It is thus concluded that both drugs Asparagus racemosus and Withania somnifera at dose 100 mg/ kg/ day, bw, p.o., is effective against gastric ulcerative rats. 50:50% mix dose of Asparagus racemosus (50 mg/ kg/ day, bw, p.o.) plus Withania somnifera (50 mg/ kg/ day, bw, p.o.) also showed significant of protection against gastric ulceration. In indomethacin (NSAID) induced gastric ulcerative model, the Asparagus racemosus was more effective as compared to only Withania somnifera extract and 50:50% mix dose of both Asparagus racemosus and Withania somnifera. Interestingly, the antiulcerogenic effect of Asparagus racemosus was closely similar to that of standard anti-ulcer drug ranitidine. Withania somnifera (100 mg mg/ kg/ day, bw, p.o.) was more effective in the ulcer produced by swim stress as compared to Asparagus racemosus 111 Book Review Title of the book : Pharmaceutical Microbiology Author : N. K. Jain Publisher : Vallabh Prakashan, Delhi Price : Rs.150 Microbiology is one of the most applied of all the biological sciences. It is one of the most essential subjects in the Pharmacy curriculum. Even though a number of books are available, there is a demand for better versions. The present book is an attempt to provide overall information to the readers interested in pharmaceutical microbiology. Although relatively concise (at 344 pages) the coverage of the subject matter is comprehensive, and provides a valuable reference source for students at undergraduate level. There are 17 Chapters in the book. Chapter 1 deals with history of microbiology. The chapter is very brief, but it covers most of the important points. Chapter 2 deals with Microbial world. It is very simple and comprehensive Bergey’s Manual is also included. Chapter 3 deals with Microbiological Methods. Staining, culture, biochemical identification and counting techniques are explained in brief. Chapter 4 on Bacteria deals with structure, classification, growth requirements and reproduction of bacteria. Chapter 5 on Fungi includes structure, reproduction and diseases caused by Fungi. Chapter 6 on virus includes general characteristics, structure, multiplication, and identification and cultivation methods. Chapter 7 deals with microbial metabolism. Chapter 8 is on Sterilization. The Chapter covers all the important methods of sterilization including their validation methods and sterility testing methods. More details could have been included. Chapter 9 is on Disinfections. The chapter includes properties, types, classification and evaluation methods. brief. Section on Emerging diseases is given. A list of all the micro organisms with the various diseases they cause could have been included. Chapter 11 on Immunology includes brief information on types of lmmunity, antigens, antibodies and antigenantibody reactions. A table explaining the Serological tests is also presented which is very simple. Chapter 12 on Immunization explains briefly about the various vaccines. Chapter 13 deals with Industrial Microbiology. The chapter includes Fermentation and production of antibiotics, vitamins and other products. The flow diagrams are quite well explanatory in nature. A section on enzymes their extraction and immobilization technique is also presented. Chapter 14 deals with Microbial transformation. It includes most of the important microbial conversion reactions. Chapter 15 deals with Pharmaceutical Biotechnology. Recombinant technology and Monoclonal Antibodies and applications of genetic engineering are explained in brief. Chapter 16 deals with Biotechnology Drugs. A brief introduction to various products is included. Chapter 17 deals with Microbiological Assays. The chapter is very comprehensive and includes assays of antibiotics and vitamins. Overall, the book is well written, interesting and clear with useful tables and figures. I would recommend this book for undergraduates for reference. Reviewed by Prof. Salma Khanam Al-Ameen College of Pharmacy Bangalore 560 027 Chapter 10 deals with Infection. The chapter is very 112 Indian J.Pharm. Educ. 39(2) April - June 2005
© Copyright 2024