1. Integrating Scientific Advances into Regulation: Pharmacogenomics and Pharmacogenetics Janet Woodcock, M.D. Director, Center for Drug Evaluation and Research April 8-9, 2003

2. Translation of innovative science to bedside medicine

3. Issue: b b New science of pharmacogenomics (and increasingly, proteomics) applied extensively in drug development b b Potential to revolutionize process b b Most of the data not seen by regulatory agencies, partly out of concern for how it will be used b b Need an approach that will enable free exchange of information, help advance the science & technology & aid in the timely development of appropriate regulatory policies

4. Background VARIABILITY IN HUMAN RESPONSE TO DRUGS: A major barrier to effective therapeutics

5. Variable Effectiveness b b For many drugs (leaving aside antibiotics, antivirals, etc)… b b Size of treatment effect from randomized trials is < 10% of outcome measure b b Many conclude that effect is “small” or that “drug doesn’t work”

6. Mean Response PlaceboDrug

7. Number of subjects DrugPlacebo Response

8. Variability in Drug Toxicity b b Drug vs placebo: each drug has consistent pattern of side effects over placebo rate. b b Observed with common as well as rare events b b Some attributable to known pharmacologic effects; others “idiosyncratic” b b Current medical approach is at the level of organ function, or is observational

9. There is an Inherited (Genetic) Component to Variability in Drug Response b b Pharmacogenomics (PG): Application of genome-wide RNA or DNA analysis to study differences in drug actions b b Pharmacogenetics : Study of genetic basis for interindividual PK differences

10. Efficacy Response: Three Types of Genetic Variables Contribute b b Genetic diversity of disease pathogenesis: cholesterol ester transfer protein ? b b Variable drug metabolism: hypermetabolizers b b Genetically based pharmacodynamic effects  -adrenergic receptor?

11. Drug Toxicity: Genetic Contributions to Variability b b Genetically based interacting state Long QT syndrome b b Differences in drug metabolism Thiopurine methyltransferase b b “Toxicodynamic” interactions Abacavir?

12. How Important are these Differences? How much of the variability will be explained by genetic differences?

13. At the Level of the Individual, a Genetic Difference may: b b Determine drug response Enzyme deficiency disease b b Highly influence drug response Polymorphic drug metabolizing enzymes

14. Individual Drug Response b However, many responses will be--- Emergent Property of multiple gene product interactions with each other and with environmental factors b Many individual genetic differences - or even patterns of differences - may have a b Many individual genetic differences - or even patterns of differences - may have a small effect on drug response

15. Oltvai and Barabasi, Science, 298, 25 Oct 02.

16. Current Drug Development b b Satisfactory determination of efficacy--but on a population basis b b Determination of drug toxicity is observational--based on animal and then human exposures b b Carcinogenic and reproductive toxicity potential based on in vitro and animal studies

17. Potential Uses of PG in Drug Development b b Improve candidate drug selection b b Develop new sets of biomarkers for toxic responses in animals and humans-- eventually minimize animal studies b b Predict who will respond to a drug b b Predict who will have serious side effects b b Rationalize drug dosing

18. Potential Impact of PG on Drug Development b b Move from current empirical process to mechanism-based process, hypothesis driven b b Lower cost, faster process resulting in more effective, less toxic drugs for smaller population

19. How is PG being used now?

20. PG and Drug Development: Discovery and Lead Candidate b b Target identification b b Evaluating cellular or animal responses to different candidates b b Not part of regulatory submissions

21. PG and Drug Development: Nonclinical b b Exploratory studies: cells and animals b b Directed studies: genes of interest b b Explanatory studies: evaluate an observed toxic response b b “Toxicogenomics”: develop predictive response patterns

22. PG and Drug Development: Human Studies b b Sort disease syndromes into subgroups based on genetic differences in pathogenesis and evaluate differential responses to treatment b b Evaluate use of genetic/phenotypic tests for metabolizer status to predict dosing

23. Human Studies b b Search for genetic differences in “responders” vs “nonresponders-- markers for different PD response b b Seek genetic explanation for severe or catastrophic side effects b b STET and gene expression screening

25. Obligations of Drug Regulators b b Determine if drug is safe and effective b b Protect human subjects enrolled in trials

26. Legal requirements: FD &C Act b b Safety: evaluate reports of “all methods reasonably applicable to show whether or not such drug is safe for use under the conditions…in the proposed labeling” b b Effectiveness: “adequate and well controlled trials” to show that “the drug will have the effect it purports to have under the conditions of use”

27. IND Submission requirements: 21 CFR 312.23(a) (8) b Pharmacology and toxicology information “on the basis of which the sponsor has concluded that it is reasonably safe to conduct the proposed clinical investigations”

28. NDA Submission requirements: 21 CFR 314.50  Nonclinical studies. d (2) (I): submit “studies that are pertinent to possible adverse effects” b Clinical d (5) (iv): submit “data or information relevant to an evaluation of the safety and effectiveness of the drug product”

29. Question b b When/how to use developing PG information in regulatory decisions? b b When is the information “reasonably applicable” to safety?” b b Under what circumstances is submission to FDA needed?

30. Proposal b b FDA will establish policies on categories of PG studies b b “Submission requirement” will be included in policy Submission not required for some types Submission required for other types Some with no regulatory impact

31. Proposal b “Regulatory impact” will be included in policy b Results from some study categories will not have any regulatory impact b Other study results will be utilized as part of safety/efficacy evaluation

32. Proposal b Possible threshold determination: Does genomic information represent valid biomarker with known predictive characteristics? b Develop threshold and policies using public and transparent process with advisory committee oversight

33. Possible Procedures b FDA would establish Interdisciplinary PG Review Group (IPGRG) b Categorization of studies and internal procedures published in guidance b Results submitted to IND or NDA as “research information package” for review by IPGRG b Periodic public re-evaluation of decision tree

34. Examples: With Regulatory Impact b b Trial enrollment by genotype: enrichment of responders avoiding bad outcomes b b Selection of dose based on metabolizer genotype

35. Examples: With Regulatory Impact (cont.) b b Safety rationale based on animal genomic data--i.e., explaining why a toxic finding is unique to that species b b In general- results intended to influence the course of the clinical development process will be considered part of the S&E evaluation

36. PG results without regulatory impact b Evaluation of new transporter gene diversity vs response in clinical subjects b Genomic SNP data collection in clinical trial subjects b Gene expression microarray screen in trial subjects b Gene expression microarray screen in animal toxicology study

37. Questions for Discussion b Is this approach reasonable? Feasible? b Will it achieve objectives Free exchange of data? Ability of FDA scientists to begin developing framework for new findings? Advance the use of the new science ? Advance the use of the new science ?