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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.

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patient selection markers in drug development programs

Patient Selection Markers in Drug Development Programs

Michael Ostland

Genentech

FDA/Industry Statistics Workshop:

Washington D.C., September 14 – 16, 2005

outline
Outline
  • Background
  • Seven Questions from a Drug Development POV
  • Concluding Remarks
background
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
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 d5
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
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
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
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
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
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
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

Positive

assay

Negative

Control

Indeterminate

Phase II Design (cont’d)

A randomized design with retrospective testing

A

Positive

assay

Negative

B

Treatment

Indeterminate

C

Enrolled Patients

randomize

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
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
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

A

Positive

Negative

B

Treatment

Indeterminate

C

Positive

D

Control

Negative

E

Indeterminate

F

decision making cont d15
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
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
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
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
Acknowledgements

Alex Bajamonde

Cheryl Jones

Lee Kaiser

Gracie Lieberman

Ben Lyons

Howard Mackey

James Reimann

Julia Varshavsky

Xiaolin Wang