PART I: RWE SERIES Providing the background, the research and the insights. REAL WORLD EVIDENCE AND WHY IT MATTERS Jan 2015 What is Real World Evidence (RWE) and what does it bring to the pharmaceutical industry? In Part I of the RWE series we introduce the ideas and concepts behind RWE, providing an overview of its role and how it fits into the industry. We explain why pharmaceutical companies are increasingly adopting RWE programmes. This is the first part of a regular series available at svmpharma.com BY GEM AUDDY [email protected] SVMPHARMA LIMITED WINCHFIELD LODGE OLD POTBRIDGE RD WINCHFIELD HAMPSHIRE RG27 8BT (+44) 01252 849071 EXT. 2068 © 2015 SVMPharma Ltd. All rights reserved. 1 The Changing NHS T he NHS is going through a period of transition that looks set to continue for several years to come. In addition to changes in infrastructure and organisation, there has been a strategic shift with the NHS demanding more value from the resources it has available and the companies it works with. Controlling expenditure on drugs and managing the size of the UK Medicines Bill is a key area of action for the NHS, and this is apparent in a number of policies which have either been recently implemented by the NHS or are in an BOTH NEW AND EXISTING DRUGS ARE advanced stage of planning (1-4). HAVING THEIR VALUE CALLED INTO As a result of these changes in the QUESTION NHS, both new and existing drugs are having their value called into question, placing certain pharmaceutical companies in a challenging position to remain competitive, and opening up new opportunities for others. Pre-launch randomised controlled trials (RCTs) are sufficient for establishing a drug’s efficacy, demonstrating safety and gaining a licence. However, it is becoming increasingly clear that drugs need to supplement this with Real World Evidence (RWE) in order to gain traction in the market and to then either grow or defend its share (5-7). Defining Real World Evidence RWE can be broadly defined as ‘the collection of data outside of conventional clinical trials in order to evaluate what is happening in clinical practice’. RWE and related methods seek to both enhance and complement existing methods of data collection (8). THE COLLECTION OF DATA OUTSIDE OF CONVENTIONAL CLINICAL TRIALS TO EVALUATE WHAT IS HAPPENING IN CLINICAL PRACTICE This data is derived from sources including patient registries, routine administrative data, observational research datasets, electronic health records and population health surveys. It is with the technological evolution and broadening scope of these data sources in recent years that RWE is ready to fulfil its potential (9). Real World Evidence through Service Evaluation KOL Identification and Mapping Healthcare Data Analytics Bespoke Market Research Hospital Episode Statistics CONTACT US © 2015 SVMPharma Ltd. All rights reserved. 2 Following the pseudonymous patient journey Data on a vast scale Judging true performance Bespoke data collection methods answering the complex questions Data on a vast scale Bespoke data collection methods answering the complex questions RWE enables analyses of study populations at a scale far beyond what would be feasible in a clinical trial. Using powerful data tools, the filtering and analyses of millions of records can be undertaken efficiently on datasets such as Hospital Episode Statistics (HES) and GP Practice Prescribing Data. These large datasets are useful for identifying unmet treatment needs, targeting patient segments and highlighting prescribing patterns; these are insights which help both the NHS & the pharmaceutical industry (10-13). Following the pseudonymous patient journey Different records from a dataset such as HES or Clinical Practice Research Datalink (CPRD) can be linked via a unique identifier whilst maintaining the patient’s confidentiality. This allows the patient journey to be followed across hospitals visits, between primary and secondary care, and along treatment pathways. This can uncover valuable information such as motivators for seeking care, triggers for switching medicines and long term compliance issues. This can be used alongside qualitative datasets such as Patient Reported Outcome Measures (PROMS) (14). Intelligent and customised RWE data collection programs can be designed alongside patient groups and healthcare professionals to focus on selected issues and fill gaps in knowledge. An online tool allows flexibility, validation and guidance in data input with real-time analysis. Complex patient histories can be streamlined and reduced to the pertinent information required, and real world scenarios can be analysed. Judging true performance It is difficult to predict how a drug will perform in the real world clinical setting. A variety of overriding factors come into play such as poor adherence, potential drug interactions due to polypharmacy, the impact of co-morbidities and how far the disease has progressed, all of which can diminish the impact of a drug or distort its effects. The collection and analysis of RWE enables stakeholders to make informed decisions throughout the product lifecycle (9, 15, 16). © 2015 SVMPharma Ltd. All rights reserved. 3 A S ELECTI ON OF RECENT YEAR TYPE LOCATION SIZE UK RW E TRI ALS Effectiveness of omalizumab in severe allergic asthma: a retrospective UK real-world study (17) 2013 Audit Efficacy and safety of canakinumab therapy in paediatric patients with cryopyrin-associated periodic syndrome: a single-centre, realworld experience (18) 2014 Observational Obtaining real-world evidence: the salford lung study (19) Ten specialist centres across the UK 136 Great Ormond Street Hospital, London 10 Salford, Greater Manchester 7000+ 2014 Pragmatic RCT RWE Success & Recognition In recent years there has been a notable increase in the publication of RWE in leading journals worldwide; this shows an important change in the acceptance and recognition of real world data. In traditional RCTs, patient selection, randomisation to groups and other controlled conditions maximise internal validity. These RCTs are essential in evaluating the clinical effectiveness and safety of drugs but there are doubts on how it can be applied to the real world clinical setting (10, 16, 20-23). A move towards RWE shifts the focus AN IMPORTANT CHANGE IN THE towards increased generalisability of the findings and ACCEPTANCE AND RECOGNITION encompasses a wide range of study designs including OF REAL WORLD DATA pragmatic RCTs, modelling analyses and observational studies (17-19, 24, 25). RWE consists of a broad and interrelated series of concepts; this introductory article has focused on insights from big data, the ability to follow a patient journey, customised data collection methods and the ability to judge true performance outside of a controlled trial. Pharmaceutical companies need to adapt to meet the changing requirements and demands of the NHS, and to effectively show the value of their products. In this competitive environment, the collection, analysis and presentation of RWE can drive success and growth. RWE is growing in importance and is set to become an essential part of the marketing and medical strategy for a successful drug. NEXT ON THE RWE SERIES JOIN US FOR PART II IN WHICH WE DETAIL THE DIFFERENT SOURCES OF RWE AND LOOK AT HOW THIS DATA CAN BE COLLECTED AND ANALYSED. VISIT SVMPHARMA.COM & FOLLOW US @SVMPHARMA © 2015 SVMPharma Ltd. All rights reserved. 4 1. Hurst J, Williams S. Can NHS hospitals do more with less?: Lulu. com; 2012. 2. Sculpher M. Value-based pricing to ensure cost effective drugs for the UK NHS: Will it work? Clinical Therapeutics.35(8):e129. 3. O’Neill P, Mestre-Ferrandiz J, Puig-Peiro R, Sussex J. Projecting Expenditure on Medicines in the UK NHS. PharmacoEconomics. 2013;31(10):933-57. 4. Wise J. NHS spending on drugs is frozen for two years under price deal2013 2013-11-07 15:12:47. 5. Epstein RS, Sidorov J, Lehner J-P, Salimi T. Integrating scientific and real-world evidence within and beyond the drug development process. Journal of Comparative Effectiveness Research. 2011;1(1s):9-13. 6. Kessler R, Glasgow RE. A Proposal to Speed Translation of Healthcare Research Into Practice: Dramatic Change Is Needed. American Journal of Preventive Medicine. 2011;40(6):637-44. 7. Propper C. Competition, incentives and the English NHS. Health Economics. 2012;21(1):33-40. 8. Garrison LP, Jr., Neumann PJ, Erickson P, Marshall D, Mullins CD. Using Real-World Data for Coverage and Payment Decisions: The ISPOR RealWorld Data Task Force Report. Value in Health.10(5):326-35. 9. Miriovsky BJ, Shulman LN, Abernethy AP. Importance of health information technology, electronic health records, and continuously aggregating data to comparative effectiveness research and learning health care. Journal of clinical oncology : official journal of the American Society of Clinical Oncology. 2012;30(34):4243-8. 15. Roski J, Bo-Linn GW, Andrews TA. Creating value in health care through big data: opportunities and policy implications. Health affairs (Project Hope). 2014;33(7):1115-22. 16. Roche N, Reddel HK, Agusti A, Bateman ED, Krishnan JA, Martin RJ, et al. Integrating real-life studies in the global therapeutic research framework. The Lancet Respiratory Medicine. 2013;1(10):e29-e30. 17. Barnes N, Menzies-Gow A, Mansur AH, Spencer D, Percival F, Radwan A, et al. Effectiveness of Omalizumab in Severe Allergic Asthma: A Retrospective UK Real-World Study. Journal of Asthma. 2013;50(5):529-36. 18. Russo RAG, Melo-Gomes S, Lachmann HJ, Wynne K, Rajput K, Eleftheriou D, et al. Efficacy and safety of canakinumab therapy in paediatric patients with cryopyrin-associated periodic syndrome: a singlecentre, real-world experience. Rheumatology. 2014;53(4):665-70. 19. New JP, Bakerly ND, Leather D, Woodcock A. Obtaining real-world evidence: the Salford Lung Study. Thorax. 2014. 20. Sanson-Fisher RW, Bonevski B, Green LW, D’Este C. Limitations of the Randomized Controlled Trial in Evaluating Population-Based Health Interventions. American Journal of Preventive Medicine.33(2):155-61. 21. Rothwell PM. External validity of randomised controlled trials: "to whom do the results of this trial apply?". Lancet. 2005;365(9453):82-93. 22. Berger ML, Lipset C, Gutteridge A, Axelsen K, Subedi P, Madigan D. Optimizing the Leveraging of Real-World Data to Improve the Development and Use of Medicines. Value in Health. (0). 10. Berger ML, Doban V. Big data, advanced analytics and the future of comparative effectiveness research. J Comp Eff Res. 2014;3(2):167-76. 23. Ware JH, Hamel MB. Pragmatic trials–guides to better patient care. N Engl J Med. 2011;364(18):16857. 11. Murdoch TB, Detsky AS. THe inevitable application of big data to health care. JAMA. 2013;309(13):1351-2. 24. Hupperts R, Ghazi-Visser L, Martins Silva A, Arvanitis M, Kuusisto H, Marhardt K, et al. The STAR Study: A Real-World, International, Observational Study of the Safety and Tolerability of, and Adherence to, Serum-Free Subcutaneous Interferon β-1a in Patients With Relapsing Multiple Sclerosis. Clinical Therapeutics. 12. Bates DW, Saria S, Ohno-Machado L, Shah A, Escobar G. Big data in health care: using analytics to identify and manage high-risk and high-cost patients. Health affairs (Project Hope). 2014;33(7):1123-31. 13. Rowlingson B, Lawson E, Taylor B, Diggle PJ. Mapping English GP prescribing data: a tool for monitoring health-service inequalities. BMJ Open. 2013;3(1). 25. Banerjee A, Lane DA, Torp-Pedersen C, Lip GY. Net clinical benefit of new oral anticoagulants (dabigatran, rivaroxaban, apixaban) versus no treatment in a'real world'atrial fibrillation population: a modelling analysis based on a nationwide cohort study. Thrombosis and haemostasis. 2012;107(3):584. 14. Black N. Patient reported outcome measures could help transform healthcare. BMJ (Clinical research ed). 2013;346:f167. © 2015 SVMPharma Ltd. All rights reserved. 5
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