Why Repurposing Works and How to Pick a Winning Drug

Why Repurposing Works and
How to Pick a Winning Drug
While Avoiding Failures
Christopher A. Lipinski
Scientific Advisor
MELIOR DISCOVERY
http://www.meliordiscovery.com/
Outline
ƒ Why Repurposing Works – Chemistry Space
ƒ Phenotypic Versus Mechanistic
ƒ Two Questions the VC Always Asks
ƒ Chemistry Information Content
ƒ Simple Computational Rankings
ƒ Medicinal Chemistry Pattern Recognition
ƒ Quality Through an Abundance of Caution
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Why Repurposing Works
ƒ PC view. HTS on 100,000’s of diverse compounds
to get a lead. Why should repurposing ever work?
ƒ 22,000 genes, > 106 proteins
ƒ How many MWT 500 compounds in a human?
ƒ 200 moles x 6.02 *1023 = 1026
ƒ Diverse compounds = 1060
ƒ Compounds / targets = 10-34 (1 hit / target)
ƒ Compounds / targets = 10-25 (1 billion hits/ target)
ƒ Truly diverse library should never give a hit.
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True Diversity Does Not Exist
ƒ HTS does indeed find hits.
ƒ True diversity does exist in silico.
ƒ True diversity does not exist
experimentally.
ƒ chemistry success bias
ƒ reagent access bias
ƒ people selection bias
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Biologically Active Space
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Chemistry Space is not Diverse
Nature: December 16, 2004
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Phenotypic Versus Mechanistic
ƒ Phenotypic screening
ƒ
ƒ
ƒ
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serendipity - no mechanistic bias
experimentally driven approach
large target opportunity space
exclusive drug discovery approach pre 1980
ƒ Chemoinformatic / bioinformatic driven
ƒ
ƒ
ƒ
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compound - target – disease information
computationally driven approach
database mining based on what is known
narrow target opportunity space
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Two Questions the VC Always Ask
#1: Failures in Phase 2 and Phase 3?
Lots of opportunity to look at late
phase efficacy failures
Why Drugs Fail – A Study on Side Effects in New Chemical Entities,
Schuster et al., Current Pharmaceutical Design, 2005, 11, 3545-3559
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Two Questions the VC Always Ask
#2: On target or off target?
ƒ On target
ƒ new indication is original mechanism
ƒ 70 – 95% based on 70 literature examples
ƒ may not need chemistry optimization
ƒ Off target
ƒ new use is by a new mechanism
ƒ may need chemistry optimization
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Chemistry Information Content
Structure in CAS
SciFinder
ƒ Cannot run any
calculations on a
picture.
ƒ Must capture the
compound structure in
machine (computer)
readable format.
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Translate into *.mol Format
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The Vioxx Connection Table
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Structure Capture Reference
http://www.accelrys.com/reference/publications/pub_lipinski.php
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SciFinder Search on Vioxx
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1480 Results by Document Type
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593 Patent Documents on Vioxx
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Vioxx Patent Year Analysis
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Sources of Clinical Data
ƒ IDDB (Thomson Scientific)
ƒ Pharmaprojects (PJB Publications)
ƒ Integrity (Prous Science)
ƒ Compendium of New Drug Approvals in eleven
industrialized countries 1970-1983 (FDA)
ƒ UN withdrawn drugs list (ISBN 92-1-130230-7)
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Indications Discovery Substrate
Pool and Stream
ƒ
IDdb references 20,000 “compounds”.
ƒ 5,000 listed “discontinued”.
ƒ 1,500 discontinued for non-safety reasons.
ƒ 500 pass Melior first-tier criteria.
ƒ Eliminate cmpnds to very well vetted targets.
ƒ COM patent expired.
ƒ Eliminate anti-infectives, anti-cancer.
ƒ Misc.
ƒ
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120 Lipinski “approvable”.
150 orally active compounds discontinued / year.
ƒ
> 10 / year are Lipinski “approvable”.
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Simple Computational Rankings
Drug-like properties
ƒ Required for an orally active drug:
ƒ soluble
ƒ permeable
ƒ metabolically stable
ƒ reaches target
ƒ sufficient concentration
ƒ sufficient duration
ƒ sufficient therapeutic ratio
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A Proliferation of Useful Rules
ƒ Rule of 5 for oral activity.
ƒ Rule of 3 for fragment screening.
ƒ Less than 10 rotatable bonds for bioavailability.
ƒ PSA < 60-70 A^2 for CNS activity.
ƒ N+O <= to 5 for CNS activity.
ƒ Log P - (N+O) is positive for CNS activity.
ƒ Log D > 0 and < 3 for good permeability.
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Rishton Filters
Drug Discovery Today, 2003, vol 8, no 2, 86-95.
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Covalent Chemistry
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GSK Filters for Reactive Groups
Strategic Pooling of Compounds for High-Throughput Screening, Hann, M.,
Hudson, B., Lewell X., Lifely, R., Miller, L., Ramsden, N., J. Chem. Inf.
Comput. Sci.; 1999; 39(5) 897 – 902
http://pubs3.acs.org/acs/journals/supporting_information.page?in_manuscript=ci990423o
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Compound Quality Filters Value Judgements
ƒ Compounds may be excluded from
screening based on value judgements:
ƒ exclude beta lactams
ƒ exclude steroids
ƒ exclude flavones
ƒ exclude phospholipids
ƒ exclude carbohydrates
ƒ exclude natural products
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HERG Activity in Older Drugs
30% of CNS compounds potentially have HERG issues.
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Medicinal Chemistry Patterns
“Reality” depiction in
chemistry is
incomprehensible to
biology / genomics.
Chemistry is much
closer to pathology than
to biology / genomics.
Graphical pattern
recognition is the forte
of chemists.
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The Amygdala and Memory
ƒ Chemists are particularly social.
ƒ Chemists are superb at pattern recognition.
ƒ Structural context of “negative” compounds
is locked into the amygdala.
ƒ Rapid effortless chemistry memory retrieval.
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An Abundance of Caution
ƒ Rules play to the probability.
ƒ Filter ruthlessly unless you are really sure.
Every compound should be pristine.
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