Patient Selection Markers in Drug Development Programs Michael Ostland Genentech FDA/Industry Statistics Workshop: Washington D.C., September 14 – 16, 2005

Outline Background Seven Questions from a Drug Development POV Concluding Remarks

Background Most drugs benefit far less than 100% of the patients who are treated. Patients who get no efficacy from a drug: Still run the risk of toxicity or side effects May miss out on a benefit they would have received had they been treated with another drug instead Add costs to the health care system Dilute efficacy estimates in clinical trials

Background (cont’d) In drug development patient selection may: Enrich a population for patients who benefit, thereby allowing a drug’s efficacy to be detected in a smaller phase III trial. (see Maitournam and Simon) Enrich a population for patients with a favorable toxicity profile, thereby improving the benefit/risk ratio. Maitournam and Simon, Statist. Med. 2005; 24:329–339

Background (cont’d) By “marker” we typically have a biomarker in mind. Namely, a characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention (Biomarkers Definitions Working Group 2001) In principle, any objectively measured baseline characteristic (or completely specified combination of multiple characteristics) could form the basis for selecting patients to be candidates to receive treatment.

Seven Basic Questions What strategic imperative for patient selection? What is the desired outcome from the development program (“Target Product Profile”)? What could phase III look like? What should phase II look like? How do results from phase II lead to decisions about the design in phase III? How many patients are needed in phase II to ensure adequate decision making? What marker and what threshold for “positive”?

Strategy for Patient Selection Patient selection for clinical drug development can proceed with one of several strategic imperatives: Efficacy: Include patients most likely to benefit Exclude patients least likely to benefit Safety: Include patients least likely to experience toxicity Exclude patients most likely to experience toxicity

Target Product Profile Establish relationship between target efficacy/safety and proportion of patients selected for treatment. e.g., How much more effective does a drug need to be if only 40% of the population can be treated? Other useful metrics possible.

Phase III Designs with Patient Selection Option 1 Standard design, except only enroll patients from marker selected population. Question What are the scientific and regulatory implications of not performing a definitive assessment of efficacy on unselected patients?

Phase III Designs (cont’d) Option 2 Enroll all patients and assay for marker. Perform two primary efficacy analyses while controlling overall type I error rate: (1) Efficacy among all patients (2) Efficacy on marker selected patients Question How does efficacy on marker unselected patients impact inference when (1) is positive?

Phase II Design Usually best to consider a randomized trial: Allows assessment of whether the marker is truly predictive of increased treatment benefit, rather than simply prognostic for good outcome. Assessment of safety with contemporaneous control arm. Ideally, one tests the marker prior to randomization and stratifies, but this may not be possible for logistic reasons.

Phase II Design (cont’d) A randomized design with retrospective testing Positive A assay Negative B Treatment Indeterminate C Enrolled Patients randomize Control assay Positive Negative Indeterminate D E F Whether patients who test “indeterminate” ultimately get treated depends on the selection strategy: exclude only those least likely to benefit (yes), or only include only those most likely to benefit (no).

Phase II to III Decision Making Broadly speaking, there are four possible decisions after a phase II trial with a patient selection marker: Proceed to Ph III in marker+ subset only Proceed to Ph III in all patients and perform two tests: in all patients and in marker+ pts Proceed to Ph III in all patients and ignore marker Do not proceed to Ph III at this time

Decision making (Cont’d) Key efficacy comparisons: A vs. D: Treatment effect among known marker positive B vs. E: Trt. effect among known marker negative (A+B+C) vs. (D+E+F): Overall treatment effect (A vs. D) vs. (B vs. E): Treatment effect by marker interaction Positive A Treatment Negative B Indeterminate C Positive D Control Negative E Indeterminate F

Decision making (Cont’d) Present the key efficacy and safety comparisons along with reasonable estimates of uncertainty Interpret results using Target Product Profile Take into account Asymmetry of the decision-making loss function Biologic plausibility Hard and fast rules for all possibilities are hard (impossible?) to come by.

Size of Phase II An area of great opportunity for statisticians Power is too rigid to be very useful Expected CI widths are hard to evaluate when several parameters are of simultaneous interest Probably want to approach it from a decision-theory point of view. But this is not trivial: The fore-mentioned lack of strictly defined decision rules makes analysis impossible Quickly approach the sort of mind-numbing complexity that confirms clinicians worst prejudices about statisticians.

Marker Selection Best to have 1 – 3 candidate markers based on biologic MOA and preclinical evidence. Then a short phase II program can be used to prospectively assess. Sometimes need to use part of phase II to screen for candidate markers, and then a subsequent clinical study (prospective or retrospective?) to validate. This is lengthier and requires care (multiplicity, cross-validation at proper level, etc.). Fortunately, a lot of smart statisticians have made good progress on these matters. Similar points apply to establishing “positive” threshold

Concluding Remarks Phase II is a critical part of clinical development when patient selection markers are considered Knowledge of the assay is helpful A clear Target Product Profile is critical Statisticians have an important role in planning and decision making in this complex, uncertain environment Planning for phase II in a way that can be usefully communicated to decision makers is an open question.

Acknowledgements Alex Bajamonde Cheryl Jones Lee Kaiser Gracie Lieberman Ben Lyons Howard Mackey James Reimann Julia Varshavsky Xiaolin Wang