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

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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.
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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?

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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
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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.

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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
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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.

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