1. Biomarkers and Surrogates: Underpinnings and Clinical Trial Applications ASENT Annual Meeting March 2009 Marc K. Walton, M.D., Ph.D. Associate Director Office of Translational Science CDER-FDA The views expressed are those of the author, and do not represent an official FDA position

2. Overview of Content & Structure  Why Bother with Biomarkers? What circumstances enable them to be useful What circumstances enable them to be useful What purposes What purposes  Why Worry with Biomarkers? How & What to worry about with biomarkers How & What to worry about with biomarkers  Qualification What is that? What is that?

3. Why Biomarkers/Surrogates?  Only clinical (i.e., functional) status is important to patients  BUT in some circumstances Inability to practicably identify disease prior to symptomatic clinical manifestations Inability to practicably identify disease prior to symptomatic clinical manifestations Inadequate ability to definitively diagnosis after disease onset Inadequate ability to definitively diagnosis after disease onset Poor ability to predict future disease course in an individual patient Poor ability to predict future disease course in an individual patient Poor ability assess changes in clinical status of patients Poor ability assess changes in clinical status of patients

4. Why Biomarkers as Outcome Assessment?  Why is clinical-only approach inadequate?  Many neurological disorders complex Pathogenesis inadequately understood Pathogenesis inadequately understood Variable manifestations from person to person Variable manifestations from person to person Dynamic – variable course within a person Dynamic – variable course within a person  Clinical outcome assessments may have flaws Difficulty in developing precise, sensitive, comprehensive assessment tools Difficulty in developing precise, sensitive, comprehensive assessment tools   Suboptimal clinical assessment of treatment effect related to the nature of the disorder  For same reasons, should not expect developing and understanding biomarkers to be simple

5. Potential uses of Biomarkers  Early (prior to clinically apparent) disease identification in patient or disease risk assessment  Diagnostic tool at initial clinical onset Definitive diagnosis at early stage Definitive diagnosis at early stage Identification of meaningfully distinct subgroups Identification of meaningfully distinct subgroups  Prediction of future course  Precise assessment of current status  All have relevance to therapeutic development

6. Biomarkers in Clinical Trials Screening or Baseline Assessment  Patient selection tool  Patient stratification tool Phase 1 Studies – Outcome Assessment  Potential to demonstrate bio-activity effect Biomarker may show early cellular effect more than a clinical outcome effect Biomarker may show early cellular effect more than a clinical outcome effect  Evidence to support devoting further resources  Assist in narrowing dose / regimen range  Biomarker vs Surrogate Endpoint A matter of terminology A matter of terminology

7. Terminology  Frequently used terms: Biomarker Biomarker Bioactivity endpoint Bioactivity endpoint Pharmacodynamic parameter Pharmacodynamic parameter Activity endpoint Activity endpoint Surrogate endpoint Surrogate endpoint  Exact meaning may vary with speaker and have differing implications

8. Terminology (cont’d)  Common themes of the varying meanings: Not a measure of clinical benefit Not a measure of clinical benefit Believed to indicate a biological effect of relevance Believed to indicate a biological effect of relevance  Important to specify to what it is relevant  Both nature and time of clinical relationship  May be thought to reflect an effect on an endpoint of direct clinical relevance  May be a phenomenon thought associated with disease process  Critical to specify the intended meaning and use

9. Phase 2 Studies – Outcome Assessment  Potential to evaluate dose-response relationship (efficacy or safety)  Use to select specific doses / regimens for detailed study  Aid to selection of patient population for detailed study  Aid to interpretation of observed clinical events  Aid estimation of sample size for Phase 3  May critically aid design of successful Phase 3 study Biomarkers in Clinical Trials

10. Phase 3 Studies – Outcome Assessment  Secondary endpoint Objective Objective Potentially precise Potentially precise Supportive of clinical efficacy endpoint Supportive of clinical efficacy endpoint Biomarkers in Clinical Trials

11. Phase 3 Studies – Outcome Assessment  Primary Endpoint  ‘Validated’ Surrogate Primary Endpoint Reliability of biomarker known Reliability of biomarker known Relationship to specific clinical outcome well established Relationship to specific clinical outcome well established Validly stands in place of clinical status Validly stands in place of clinical status For the specific disease/condition being studied For the specific disease/condition being studied For the specific intervention being studied For the specific intervention being studied Biomarkers in Clinical Trials

12. Phase 3 Studies – Outcome Assessment  Unvalidated Surrogate Primary Endpoint Requires strong, but not definitive understanding of clinical relationship Requires strong, but not definitive understanding of clinical relationship Accelerated Approval provisions of regulations Accelerated Approval provisions of regulations  Special circumstances for drug approval based on unvalidated surrogate

13. Potential Advantages of Activity Measures  May be more rapidly observed than clinical outcome Shorter clinical trial Shorter clinical trial  May be easier to measure Greater compliance in obtaining accurate measure Greater compliance in obtaining accurate measure  Lesser intrinsic variability than a clinical measure Smaller sample size Smaller sample size  More objective measure Accurate results (unbiased) Accurate results (unbiased)  Less expensive to measure Less costly clinical program Less costly clinical program

14. Potential Hazards of Activity Measures  May Mislead – Disparity with clinical outcome False impression of existence/absence of benefit False impression of existence/absence of benefit Incorrect Dose / Regimen / Population selection Incorrect Dose / Regimen / Population selection Incorrect estimate of size of benefit Incorrect estimate of size of benefit Incorrect estimate of frequency of benefit Incorrect estimate of frequency of benefit  May result in failed trial for an effective drug  Nature of risk from being mislead dependent upon how critical are the resulting decisions  Cause of divergence Alternate mechanisms of action of the intervention Alternate mechanisms of action of the intervention Shape of the surrogate-clinical relationship Shape of the surrogate-clinical relationship

15. Understanding the Surrogate Measure: Idealized

16. Understanding the Surrogate: Silent Surrogate

17. Understanding the Surrogate: Complexity Surrogate Endpoint Drug Intervention Clinical Outcome Sequential Order of Processes P1 P2 P3 Surrogate Endpoint Drug Intervention Clinical Outcome P1 P2 P3

18. Understanding the Surrogate Measure Clinical Status Biomarker

19. Understanding the Surrogate Measure: Idealized

20. Understanding the Surrogate Measure C2C2 C3C3 C4C4 C5C5 C1C1 Clinical Status Biomarker Status b1b1 b2b2

21. Understanding the Surrogate: Complexity Surrogate Endpoint Drug Intervention Clinical Outcome Sequential Order of Processes P1 P2 P3 Surrogate Endpoint Drug Intervention Clinical Outcome P1 P2 P3

22. Understanding the Surrogate Measure: Potential Consequence of Complexity C2C2 C1C1 Clinical Status Biomarker Status b1b1 b2b2

23. Understanding the Surrogate Measure: Precision of Knowledge Clinical Status Biomarker Status b1b1 b2b2 b3b3

24. Biomarker Qualification  Qualification vs. Validation  Developing FDA Program  Outgrowth of Critical Path Initiative Particularly for biomarkers expected to have repeated application in drug development & evaluation Particularly for biomarkers expected to have repeated application in drug development & evaluation

25. Biomarker Qualification  Definition: The conclusion that within the stated context of use, the results of biomarker measurements can be relied upon to have a stated interpretation and utility. Change in term aids awareness of need for specificity Change in term aids awareness of need for specificity  Regulatory implication: Industry can rely upon using the biomarker in the approved manner in the IND period, and in NDA and BLA submissions, without needing to request that the relevant CDER review group consider and reconfirm the biomarker.

26. BQ Usage  The use of a qualified biomarker can be applied in drug development and evaluation if there are NO: Serious study flaws (e.g., unverifiable data, improper performance of assays, etc.) Serious study flaws (e.g., unverifiable data, improper performance of assays, etc.) Attempts to apply the biomarker outside the qualified (i.e., approved) context of use Attempts to apply the biomarker outside the qualified (i.e., approved) context of use New and conflicting scientific facts not known at the time the qualification was granted New and conflicting scientific facts not known at the time the qualification was granted

27. Biomarkers at FDA  Ad hoc Context of use always drug-dependent Context of use always drug-dependent During drug development and approval During drug development and approval Labeling updates (e.g., pharmacogenomic) Labeling updates (e.g., pharmacogenomic)  Drug/Diagnostic co-development  Biomarker Qualification Process (BQP) Coordinated policy Coordinated policy

28. BQ Program in Spectrum of Biomarker Efforts  Early Biomarker Development  Late Biomarker Development Engaged with BQ Program Engaged with BQ Program  Other Initiatives FDA collaborates with

29. BQ Process  A framework for interactions between CDER and biomarker sponsors so that CDER can guide them towards compiling comprehensive evidence to support qualification of their selected biomarker(s)  A mechanism enabling CDER to have a well-organized and center-wide unified, formal review of the data supporting a biomarker, eventually leading to a CDER decision to qualify or not  Enables a publicly available and scientifically well- supported statement by CDER of biomarker qualification providing confidence that the evaluation has been comprehensive and the conclusions can be relied upon

30. Process within FDA  ‘Sponsor’ brings project to FDA  Interdisciplinary working team assembled within CDER & FDA  Information Package reviewed  Advice as needed on how to further progress development for intended use Ultimately development is thought complete Ultimately development is thought complete  Full review and decision on qualification  Formal statement of qualification granted if appropriate