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Janet Woodcock, MD Director, Center for Drug Evaluation and Research Food and Drug Administration

Today ’ s Biomedical Innovation: “ Lost in Translation”?. QB3 Entrepreneurs ’ Discussion University of California, San Francisco Thursday, April 26, 2012. Janet Woodcock, MD Director, Center for Drug Evaluation and Research Food and Drug Administration.

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Janet Woodcock, MD Director, Center for Drug Evaluation and Research Food and Drug Administration

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  1. Today’s Biomedical Innovation: “Lost in Translation”? QB3 Entrepreneurs’ Discussion University of California, San Francisco Thursday, April 26, 2012 Janet Woodcock, MD Director, Center for Drug Evaluation and Research Food and Drug Administration

  2. Will New Scientific Discoveries Revolutionize Treatment of Disease (Soon)? • Advances in both science and technology are providing unprecedented opportunities for new approaches to disease prevention, diagnosis and treatment • However, in some senses, the barriers to successful development have never been higher • New paradigms for evaluation of diagnostic and therapeutic interventions must be developed • Faster • More efficient • But equally or more informative

  3. Drug Development Currently takes more than 10 years and requires an investment of over $1B to bring a single innovative drug to market Clinical investigation, premarket application, and postmarket stages are heavily regulated in most developed countries Ongoing concern about ability of the drug development enterprise to translate innovative science and bring needed therapies to market Ongoing concern about the ability, and willingness, of societies to pay for novel therapies

  4. DRUG DISCOVERY PRE CLINICAL CLINICAL TRIALS FDA REVIEW LARGE SCALE MFG 5,000-10,000 COMPOUNDS 250 ONE FDA- APPROVED DRUG 5 PRE-DISCOVERY PHASE 4: POST MARKETING SURVEILLANCE NDA SUBMITTED TO FDA IND SUBMITTED TO FDA PHASE 1 PHASE 2 PHASE 3 Number of Volunteers 20-100 100-500 1000-5000 3-6 YEARS 6-7 YEARS 0.5-2 YEARS Research and Development Process SOURCE: PhRMA 2008, Stages of Drug Development Process and attrition rate of compounds as they travel through the drug development process over time.

  5. For 12 PhRMA companiesResearch Spending vs New Drugs Approved during the Period 1997-2011

  6. Private & PublicResearch and Development Spending Source: Burrill & Company, PhRMA, NIH Office of Budget

  7. FDA NME Approvals • Basically stable output over long term (vs increased investment in basic research and R&D) • Decline from late 1990s reflects primarily decrease in submission of “me-too” drugs: now difficult to get on formulary • FDA seeing increased novelty in applications over recent 5 year period; more “game-changing” therapies • Possibly reflects adjustment of industry strategies • PDUFA program (currently up for re-authorization) ensures that review times are relatively predicatable

  8. In 2011, CDER approved 30 NMEs,the highest total of NMEs approved in seven years *The final number of NME Applications filed in 2011 is projected, pending final validation of the data and dependent outcome of 12 applications submitted in late 2011.

  9. CDER met review goal datesfor 97% of the new molecular entities approved in 2011 Met PDUFA Target Dates Adcetris Arcapta Benlysta Brilinta Caprelsa Darilesp Datscan Dificid Edarbi Edurant Eylea Ferriprox Firazyr Gadavist Horizant Incivek Jakafi Natroba Nulojix Onfi Potiga Tradjenta Victrelis Viibryd Xalkori Xarelto Yervoy Zelboraf Zytiga First Cycle Approval Adcetris Benlysta Caprelsa Dificid Edarbi Edurant Erwinaze Eylea Gadavist Incivek Jakafi Onfi Tradjenta Victrelis Viibryd Xalkori Yervoy Zelboraf Zytiga

  10. Innovation in drug approvals for 2011 Approved First in the U.S. Adcetris Benlysta Caprelsa Dificid Edarbi Edurant Eylea Incivek Horizant Jakafi Natroba Nulojix Tradjenta Victrelis Viibryd Xalkori Yervoy Zelboraf Zytiga Orphan Drug Approvals Adcetris Caprelsa Erwinaze Ferriprox Firazyr Jakafi Nulojix Onfi Xalkori Yervoy Zelboraf First in-Class Drugs Adcetris Benlysta Darilesp Firazyr Jakafi Nulojix Potiga Victrelis Xalkori Yervoy Zelboraf Zytiga

  11. Role of Regulatory Standards • Certainly some of the costs are driven by increased expectations—over the last several decades--about evaluating the performance of the drug (both for safety and efficacy) before it goes on the market • Even after an expenditure of $1B per successful drug, multiple important clinical questions remain unanswered (e.g. dose and regimen, use with other therapies, optimal duration of therapy, consequences of long-term use) • Academic clinical community constantly clamors for more data to be generated premarket and postmarket • Payer community has rising expectations—e.g., Europe

  12. Key Issues • How to balance information needs of prescribers, patients and payers against desire for speedy access to better therapies (more effective, less toxic etc.) on the part of prescribers and patients? • How to keep the biomedical innovation sector alive with a viable business model, but also keep new innovations affordable for society? • How to translate the vast amount of new knowledge about human health and disease efficiently, rather than using the time-consuming, costly and inefficient methods currently in place? • Is there a more prominent role for the academic biomedical sector?

  13. Can the Academic Biomedical Sector Become a more Integral Part of the DrugDevelopmentEcosystem?

  14. Background: A Very Long Time Ago Professors were engaged in drug discovery (and experimented upon themselves and their grad students) Industry commercialized discoveries Industry largely unregulated

  15. Background: 1950-60s Growth of mainstream (and other) pharmaceutical houses 1000’s of unstudied, possibly ineffective drugs on the market Start of a long period of seminal drug discoveries: cardiovascular disease; infectious disease; cancer; psychiatric disorders Beginning of the requirement to show drug efficacy (1962)

  16. “Modern Era” • Huge pharmaceutical companies: massive “fully integrated” drug discovery and development enterprises • Academic focus on molecular biology of health and disease: “basic biomedical science” • Outpouring of novel therapies and also x’s in a class (e.g., 17 NSAIDS) • Society increasingly less impressed with novelty • Decreased tolerance of uncertainty • Regulators respond with more testing requirements • Cost effectiveness questions arise

  17. Now • Pharmaceutical industry: progressively greater investment and diminished return • Biotech: success, but can society afford the products? • Venture capital: fleeing medical products sector • Academia: 30 year investment in biomedical research sector—will funding keep rising? What is the academic role in translational research? • Regulators blamed for: • Current problems in drug development • Excess conservatism • Excess enthusiasm

  18. Current Government and Industry Roles in Pharmaceutical Research & Development

  19. Future: Opportunities for New Roles and Relationships to Improve Process • Pharmaceutical Sector Competencies • Rigor • Medicinal chemistry • High throughput screening • Lead optimization • Manufacturing and scale up • Late phase development • Marketing and distribution

  20. Future: Potential Shift in Roles? • Academic Strengths • Molecular biology of target; pathways; pathogenesis • Animals and in vitro models and testing scenarios; in depth disease understanding • Relationships with relevant patients • Proximity of patients and laboratory

  21. Future Role of Academia in Drug Discovery and Development Partnering with industry in discovery and translation of specific products or therapeutic areas Research leading to new evaluative tools for predicting, understanding and assessing the effects of medical products in the relevant species (people) Hubs for clinical trial networks that incorporate community practitioners and also have the capacity for integration of sophisticated bench science

  22. Role of Academia: Urgent Need for New Evaluative Tools • Drug manufacturing and scale up • Multiple academic consortia working on this; poorly funded • Safety evaluation: little changed in decades • Traditional empirical evaluation in animals • Human safety evaluation a “side effect” of efficacy evaluation • Efficacy evaluation: Predicting and confirming efficacy still a huge challenge; generally still empirical • Affects academic efforts as well as industrial • Many late failures due to efficacy problems

  23. Discovery and Translation of Specific Innovations • “Academic based drug development” • Thousands of less common disorders that are not subject to industrial development • Specific pathways or mechanisms that have been the subject of extensive research in a particular laboratory • Early bench to bedside translation • Proof of concept studies • Pharmacodynamic evaluations

  24. Streamlining the Bench to Bedside Transition • “Exploratory IND” guidance • Tailor required toxicology studies to proposed investigations • Can be significantly reduced for single dose or microdose trials, or brief administration • Phase 1 trial cGMPs • Remove phase 1 clinical trial material from extensive cGMP requirements in regulations • These were written for commercial products • Companion guidance: ability to use laboratory produced material with specific safeguards

  25. Development of Evaluative Tools:A Tremendously Neglected Area • Better science is needed to both predict and assess safety and efficacy of investigational products • Now: “Build an airplane and then see if it can fly” • Major causes of failure in Phase 3 clinical development • Lack of effectiveness against placebo or active • Unexpected drug toxicity • Commercial non-viability (not better than existing therapy)

  26. Evaluative Tools • Current drug development might be viewed as what physics would be without engineering • Large amount of biochemical knowledge but few ways to assess state of whole organism and impact of interventions at the organism level • Most assessment tools are not standardized so limited ability to compare one experiment to another • Little insight into sources of variability of treatment response, even current therapies • As a result, most clinical development programs are “brute force” empirical efforts: extremely costly and time-consuming

  27. Safety Evaluation: Opportunities • Routine rat or dog studies good for predicting safe first-in-human dose but not for understanding less common toxicities • Structure Activity Relationships • FDA has collaborated to make some screening programs available that correlate computer readable structural motifs with known animal or clinical adverse outcomes from FDA databases • Opportunities to link structure with other assays that are becoming available and also do more extensive link to clinical data

  28. Safety Evaluation: Opportunities • Systems biology approach to drug toxicity • Screens for off-target receptor binding • Gene expression in response to drug exposure: safety pharmacogenomics • Cellular systems for assessing drug responses broadly • Human pharmacogenomics: not just drug metabolism • Allelic variability in drug target • Uncommon alleles increasing risk of major drug toxicity

  29. Development of Biomarkers for Prediction of Safety or Efficacy • Many potential biomarkers discovered in academic laboratories but never understood sufficiently for: • Use in drug development • Regulatory decision making • FDA attempting to introduce more rigorous process as part of “Critical Path Initiative” • FDA Guidance on “Drug Development Tools” qualification process: US and EU will work with groups on qualifying new tools for use in drug development • A central role for academic scientists

  30. Predicting, Measuring, and Improving Efficacy • New endpoints • New trial designs • Use of biomarkers to subset disease ( prognostic or response predictors) • Jupitor trial (C-reactive protein; rosuvastatin) • Screening tumors for activating pathways • Known as “enrichment”, CDER guidance • Use of patient-reported outcomes • Conducting natural history studies to understand disease course—particularly in rare diseases

  31. New Endpoints Foundation for the National Institutes of Health (FNIH) Scientific work on endpoints and clinical trial designs FNIH and the Biomarkers Consortium are developing endpoints for clinical trials in skin infections and community acquired pneumonia Helps reduce uncertainty around using a new endpoint or trial design Includes academia, industry, IDSA, NIH, and FDA

  32. New Endpoints in Pain Trials Why ACTION? Clinical studies, particularly efficacy trials, notoriously flawed for analgesic drug development Frequent failed studies with drugs known to be effective Extremely small treatment effects even when successful Multiple causes, e.g.: Large placebo effect Missing data Study design flaws Study analysis flaws Investigator quality Frequent use of foreign sites

  33. New Endpoints Innovative clinical trial design to facilitate schizophrenia drug development… FDA and National Institute of Mental Health (NIMH) “MATRICS” clinical trial guidelines designed to facilitate novel compound development to treat cognitive impairment from schizophrenia (MATRICS) clinical trial guidelines for cognitive-enhancing drugs in schizophrenia

  34. Developing New Biomarkers and Patient Reported Outcomes Measures (PROs) C-Path Institute (nonprofit): submitted new biomarkers for drug induced kidney injury (data produced by a consortium); FDA and EMA accepted; undergoing clinical evaluation PROMIS (NIH PRO effort) C-Path Institute: PROs for specific diseases for qualification

  35. Quantitative Disease-Drug-Trial Models Diverse Expertise Disease Model Drug Model Trial Model FDA Data • Biology • Natural Progression • Placebo • Biomarker-Outcome • Pharmacology • Effectiveness • Safety • Early-Late • Preclinical-Healthy-Patient • Patient Population • Drop-out • Compliance Disease-drug-trial models are mathematical representations of the time course of biomarker-clinical outcomes, placebo effects, drug’s pharmacologic effects and trial execution characteristics for both the desired and undesired responses, and across experiments. Physiology

  36. Quantitative Disease-Trial Models:Alzheimer Disease Diverse Expertise FDA Data Disease Model Trial Model • Natural Progression • Placebo Response • Patient Population • Drop-out Physiology

  37. Adaptive Design with Biomarkers I-Spy 2: screening trial for investigational breast cancer drugs Biomarker Consortium--- public/private partnership: FDA / NIH / PhRMA companies Attempts to identify biomarker-defined response subgroups Adaptive design against standard-of-care Ability to screen multiple investigational agents in one trial Selected compounds could have rapid route to accelerated approval based on larger trial in responsive subgroup

  38. Re-engineering the Clinical Research Enterprise • Currently, clinical research is: • Extremely expensive • Unpleasant for most participants • Inefficient • Not totally reliable • Unavailable for the vast majority of patients (e.g., cancer patients)

  39. Clinical Research in Drug Development • Unique clinical trial at multiple stages of development • New investigators, support personnel, unique CRFs • Long lead time to set up • Frequently slow recruitment, many sites fail to recruit adequately • Lack of involvement of community practitioners, so that available universe of patient limited, often sites are competing for patients for several protocols • Rapid movement of clinical trials in drug development overseas

  40. How to Address Problem? • Consider clinical trial networks with the capacity to perform multiple trials • Include community practitioners with appropriate logistical support • Academic medical centers as hubs • Standardized CRF templates for much of data collection • Ultimately improve quality of data, involve community in clinical research

  41. The Clinical Trials TransformationInitiative (CTTI) Formed in 2008 FDA and Duke University - founding members of a public-private partnership Members include stakeholders from government, industry, academia, patient and consumer representatives, clinical investigators, professional societies, and clinical research organizations

  42. CTTI Current Projects Improving the public interface for use of aggregate data in clinicaltrials.Gov Site metrics for study start up Building quality in Use of central IRB for multicenter clinical trials Sponsor Patient Investigator IND Safety Reporting

  43. Summary There are major problems with current drug development paradigms New scientific knowledge provides huge opportunity for improvement The biomedical research community should have a greater role in many aspects of drug discovery and development Future drug development must include many innovative partnerships The clinical research enterprise in the US must be transformed

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