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Patient Selection Markers in Drug Development Programs

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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 – PowerPoint PPT presentation

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Title: Patient Selection Markers in Drug Development Programs


1
Patient Selection Markers in Drug Development
Programs
  • Michael Ostland
  • Genentech

FDA/Industry Statistics Workshop Washington
D.C., September 14 16, 2005
2
Outline
  • Background
  • Seven Questions from a Drug Development POV
  • Concluding Remarks

3
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

4
Background (contd)
  • In drug development patient selection may
  • Enrich a population for patients who benefit,
    thereby allowing a drugs 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
24329339
5
Background (contd)
  • 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.

6
Seven Basic Questions
  1. What strategic imperative for patient selection?
  2. What is the desired outcome from the development
    program (Target Product Profile)?
  3. What could phase III look like?
  4. What should phase II look like?
  5. How do results from phase II lead to decisions
    about the design in phase III?
  6. How many patients are needed in phase II to
    ensure adequate decision making?
  7. What marker and what threshold for positive?

7
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

8
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.
9
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?

10
Phase III Designs (contd)
  • 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?

11
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.

12
Phase II Design (contd)
  • 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).
13
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

14
Decision making (Contd)
  • Key efficacy comparisons
  • A vs. D Treatment effect among known marker
    positive
  • B vs. E Trt. effect among known marker negative
  • (ABC) vs. (DEF) 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
15
Decision making (Contd)
  • 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.

16
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.

17
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
18
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.

19
Acknowledgements
Alex Bajamonde Cheryl Jones Lee Kaiser Gracie
Lieberman Ben Lyons Howard Mackey James
Reimann Julia Varshavsky Xiaolin Wang
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