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Discover the complexities of drug discovery through a lens of incentives and culture, exploring the difficulties faced by academia. Learn about Blueprint Neurotherapeutics Network and how incentives can drive predictable results in drug development.
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Rigor Through the Lens of Drug Discovery and Development The game Culture and incentives Our experiences
Drug Discovery Components: It takes a village • Biological target (clear link to disease), tractable • Predictive in vitro assays that allow decision making • Animal models of disease progression and/or symptoms: Often not validated, low volume, inconsistent • Tractable chemical matter: SAR, solubility, crystallinity • ADME and safety • Intellectual property • Identification of an accessible clinical population • Objective clinical endpoints: dose setting, proof of concept, registration. Drug discovery is difficult, multi-factorial, expensive, and tedious
Why is it difficult for academics to do drug discovery and development? • Resources: Money, time, and access to multiple non-academic skill sets • Incentives/ Culture
Incentives • Feakanomics (Steven Levitt and Stephen Dubner) • “Incentives are the cornerstone of modern life…and understanding them is the key to solving just about any riddle.” • “There are three flavors of incentives: economic, social, and moral. • Academic and Industrial cultures/ incentives traditionally differ • Academia: novelty, publication (patent)/ shared results, recognition, shorter time horizon. Objective: new knowledge • Industry: novelty (exclusivity), patent/secrecy (publication), drug’s progress over time (longer time horizon). Objective: clinical compound • Challenge: How can you change the incentives and resources for academics to get the desired results: credible and predictable data that leads eventually to clinical trial.
Blueprint Neurotherapeutics Network: Scope BlueprintNeuRx 16 NIH Institutes and Centers Participate (NINDS, NCRR, NEI, NIA, NIAAA, NICHD, NIDA, NIDCD, NIEHS, NIMH, etc) Target ID Assay Screening Proof of Concept Lead Optimization Candidate Selection Pre-clinical Safety Clinical Trials R01s Molecular Libraries NIH RAID R01s Blueprint Neurotherapeutics Industry Active Small molecule Phase I Clinical Success Early chemical matter -> Chemical optimization -> Pre-IND -> Phase 1 -> License
Blueprint: Virtual Pharma Model • Solicit investigator-initiated ideas (U01 RFA) • Novel/ interesting drug targets • Strong disease assays and models • Blueprint provides industry expertise • Industry-standard contract services • Industry-seasoned advisors and consultants
BP Learnings: What is important? • A clinical path. Target candidate profile and Alice • Predictive power and throughput of the primary and secondary assays. • Tractable chemical matter: Potency, efficacy, SAR, ADMET, IP • Credible and predictive in vivo model • Formulation for in vitro and in vivo work • Key skills on or accessible to teams: biology, medchem, adme, safety, intellectual property, formulation • Clear, measurable and meaningful milestones. Gating and review • Jeffersonian triage • IP and partnering What is not a factor in approving a project: Market size, past drug development experience
PKD Foundation Experience • Disease: chronic, proliferative, inflammatory • Clinical outcome: transplant • Therapy: chronic, safe, disease modification • Strategy: Repurposing • Compound choice: candidate, logical target, safe enough, PK • Carrot for industry: no upfront cost • Tactic: Funded CRO (models: 2 mouse, 1 rat) • Why CRO: Consistency (standardization), confidence in result, confidential, cost, choice of compound • Outcome first 12 months: one impressive result, pitch to major donors ($)
