Impact of Dose Selection Strategies on the Probability of

Success in the Phase III

Zoran AntonijevicSenior Director

Strategic Development, Biostatistics

Quintiles, Inc.

Other Contributors

Frank Bretz, Novartis

Alex Dmitrienko, Ely Lilly and Company

Vlad Dragalin, Wyeth

Parvin Fardip, Wyeth

Chyi-Hung Hsu, Novartis

Tom Parke, Tessella

Jose Pinheiro, Novartis

1. Introduction

2. Design/Methods

3. Results/Discussion

4. Conclusions

Introduction

• Selection of dose(s) to advance into the Phase III is one of the most challenging decisions during drug development

• It is believed by many that high attrition rate in the Phase III is largely driven by inadequate dose selection

Introduction

• Adaptive Dose-Ranging Studies (ADRS) group formed within PhRMA to develop new and evaluate existing adaptive dose-ranging methods and strategies

• This workstreem was formed within the ADRS with a task to assess the impact of dose-selection methods/strategies on the success of the Phase III program

Key Issues for Adaptive Dose-Ranging Study Design

• Most appropriate method/design; impact on the PoS, logistics, and cost

• Number of doses to be studied,

• Number of interim looks,

• Optimal size of the Phase II relative to the size of the Phase III,

• Dose-selection criteria for the Phase III

• Number of doses to take into the Phase III

Approach

• Compare designs/strategies based on the Phase III outcome • Measured as the probability of regulatory

approval• Measured as the Net Present Value (NPV), or

some other financial measurement

Objectives• Assess the impact of different dose-

selection methods in the Phase II trials on the PoS in the Phase III • PoS defined as probability of drug approval

• Assess the impact of the Phase II sample size, and number of doses studied on the PoS in the Phase III

• Compare the performance of Phase III studies with one vs. two active arms

1. Introduction

2. Design/Methods

3. Results/Discussion

4. Conclusions

Endpoint

• Change from baseline to Week 6 in a VAS scale of pain.

• The VAS takes values between 0 (no pain) and 10 (highest pain) on a continuous scale.

Phase II Design and Assumptions

• 5 or 9 equally spaced dose levels• 0=placebo; 2, 4, 6, and 8 active• 0=placebo; 1, 2,…, 8=active

• Dose-response profiles • Linear• Logistic • Quadratic• Emax

• Sample sizes of 150 and 250 total

Efficacy Dose-Response Profiles

-1.5

-1.0

-0.5

0.0

0 2 4 6 8

Linear Logistic

Umbrella

-1.5

-1.0

-0.5

0.0

0 2 4 6 8

Emax

Dose

Exp

ect

ed

ch

an

ge

fro

m b

ase

line

in V

AS

at

We

ek

6

Safety Penalty Function

6

8

10

12

2 4 6 8

Linear Logistic

Umbrella

6

8

10

12

2 4 6 8

Emax

Dose

Pro

ba

bili

ty o

f S

AE

(%

)

Dose Selection Methods

• ANOVA with Dunnett’s adjustment• Flexible design (response-adaptive allocation)

• GADA: Bayesian adaptive dose allocation method• D-opt: adaptive dose allocation based on the D-opt

criterion• Flexible analysis

• MCP-Mod; combination of modeling and multiple comparison procedure

• Multiple Trend Test• Bayesian model averaging• Nonparametric linear regression fitting

Phase III Design

• Designs with one or two arms of the test drug were considered

• Success measured as one positive pivotal trial at two sided α=0.05

• For design with two active dose arms Dunnett’s procedure applied to control for multiplicity

Phase III Sample size

• For one active arm study N=86 per arm• ∆=1.3; σ=2.6; power 90%

• For two active arms study N=99 per arm• ∆1=1.3; ∆2=inf. σ=2.6; power 90%

• Dunnett adjusted

Dose Selection Strategy

• For Phase III design with one active dose, select dose closest to the target efficacy (∆=1.3)

• For Phase III design with two doses of active, the first dose was selected as described above

• Second dose selected is the one closer to the target efficacy between doses immediately above and below the first selected dose

Methods - Efficacy

• For each selected dose and dose response model we know the “true” treatment effect.

• For a given design of the Phase III program (sample size, sig. level for test…) we can determine the associated power corresponding to the “true” effect

Methods - Safety

• Likewise, for an assumed safety dose-response model (probability of having unacceptable safety in the trial) we can also determine the probability of failing for safety for each dose.

Methods - PoS

• Assuming that efficacy and safety successes are independent the probability of a successful Phase III program for a given dose/model combination is:         Prob(success|d,m) = [(power(dose,m) * (1 - safety.prob(dose))]

1. Introduction

2. Design/Methods

3. Results/Discussion

4. Conclusions

Probability of Success for Efficacy

ANOVA

Dopt

GADA

MCPMod

MTT

BMA

LOCFIT

70 80 90

logisticN = 150

umbrellaN = 150

70 80 90

linearN = 150

EmaxN = 150

ANOVA

Dopt

GADA

MCPMod

MTT

BMA

LOCFIT

logisticN = 250

70 80 90

umbrellaN = 250

linearN = 250

70 80 90

EmaxN = 250

Average power (%)

1 dose 2 doses

Probability of Acceptable Safety Profile

ANOVA

Dopt

GADA

MCPMod

MTT

BMA

LOCFIT

75 80 85 90

logisticN = 150

umbrellaN = 150

75 80 85 90

linearN = 150

EmaxN = 150

ANOVA

Dopt

GADA

MCPMod

MTT

BMA

LOCFIT

logisticN = 250

75 80 85 90

umbrellaN = 250

linearN = 250

75 80 85 90

EmaxN = 250

Average safety probability (%)

1 dose 2 doses

Overall Probability of Success

ANOVA

Dopt

GADA

MCPMod

MTT

BMA

LOCFIT

55 60 65 70 75 80

logisticN = 150

umbrellaN = 150

55 60 65 70 75 80

linearN = 150

EmaxN = 150

ANOVA

Dopt

GADA

MCPMod

MTT

BMA

LOCFIT

logisticN = 250

55 60 65 70 75 80

umbrellaN = 250

linearN = 250

55 60 65 70 75 80

EmaxN = 250

Average success probability (%)

1 dose 2 doses

Discussion

• PoS slightly (but consistently) better for Phase II design with 250 patients vs. 150 patients

• Methods with response-adaptive randomization component, particularly GADA, consistently outperform other designs on the overall PoS• These designs are also generally less

affected by the Phase II sample size

Discussion

• Design with two doses improves the probability of a positive efficacy result• This is not surprising given the sample size

calculation method

• This design also improves the chance of selecting at least one safe arm due to the “distribution of risk”

• Resulting PoS for two active doses improved over design with one active dose

Probability of Success for Efficacy

ANOVA

Dopt

GADA

MCPMod

MTT

BMA

LOCFIT

70 80 90

logistic1 dose

umbrella1 dose

70 80 90

linear1 dose

Emax1 dose

ANOVA

Dopt

GADA

MCPMod

MTT

BMA

LOCFIT

logistic2 doses

70 80 90

umbrella2 doses

linear2 doses

70 80 90

Emax2 doses

Average power (%)

nDose = 5 nDose = 9

Probability of Acceptable Safety Profile

ANOVA

Dopt

GADA

MCPMod

MTT

BMA

LOCFIT

70 75 80 85 90

logistic1 dose

umbrella1 dose

70 75 80 85 90

linear1 dose

Emax1 dose

ANOVA

Dopt

GADA

MCPMod

MTT

BMA

LOCFIT

logistic2 doses

70 75 80 85 90

umbrella2 doses

linear2 doses

70 75 80 85 90

Emax2 doses

Average safety probability (%)

nDose = 5 nDose = 9

Overall Probability of Success

ANOVA

Dopt

GADA

MCPMod

MTT

BMA

LOCFIT

55 60 65 70 75 80

logistic1 dose

umbrella1 dose

55 60 65 70 75 80

linear1 dose

Emax1 dose

ANOVA

Dopt

GADA

MCPMod

MTT

BMA

LOCFIT

logistic2 doses

55 60 65 70 75 80

umbrella2 doses

linear2 doses

55 60 65 70 75 80

Emax2 doses

Average success probability (%)

nDose = 5 nDose = 9

Discussion

• For a fixed sample size (N=250) design with 5 doses performed better on the overall PoS than design with 9 doses, other than for response-adaptive designs (GADA & Dopt)

• For GADA & Dopt designs with 5 and 9 doses performed similarly

Discussion

• Power for efficacy, safety, as well as the overall PoS better for the Phase III design with two active doses, whether 5 or 9 doses were studied in the Phase II

Distribution of Selected Dose

0

20

40

60

2 4 6 8

ANOVA5 doses

Dopt5 doses

2 4 6 8

GADA5 doses

MCPMod5 doses

2 4 6 8

MTT5 doses

BMA5 doses

2 4 6 8

LOCFIT5 doses

ANOVA9 doses

2 4 6 8

Dopt9 doses

GADA9 doses

2 4 6 8

MCPMod9 doses

MTT9 doses

2 4 6 8

BMA9 doses

0

20

40

60

LOCFIT9 doses

Dose selected

% T

ria

ls

Logistic, N = 250

Distribution of Selected Dose

0

10

20

30

40

2 4 6 8

ANOVA5 doses

Dopt5 doses

2 4 6 8

GADA5 doses

MCPMod5 doses

2 4 6 8

MTT5 doses

BMA5 doses

2 4 6 8

LOCFIT5 doses

ANOVA9 doses

2 4 6 8

Dopt9 doses

GADA9 doses

2 4 6 8

MCPMod9 doses

MTT9 doses

2 4 6 8

BMA9 doses

0

10

20

30

40

LOCFIT9 doses

Dose selected

% T

ria

ls

Linear, N = 250

Distribution of Selected Dose

0

10

20

30

40

50

2 4 6 8

ANOVA5 doses

Dopt5 doses

2 4 6 8

GADA5 doses

MCPMod5 doses

2 4 6 8

MTT5 doses

BMA5 doses

2 4 6 8

LOCFIT5 doses

ANOVA9 doses

2 4 6 8

Dopt9 doses

GADA9 doses

2 4 6 8

MCPMod9 doses

MTT9 doses

2 4 6 8

BMA9 doses

0

10

20

30

40

50

LOCFIT9 doses

Dose selected

% T

ria

ls

Umbrella, N = 250

Distribution of Selected Dose

0

10

20

30

40

50

2 4 6 8

ANOVA5 doses

Dopt5 doses

2 4 6 8

GADA5 doses

MCPMod5 doses

2 4 6 8

MTT5 doses

BMA5 doses

2 4 6 8

LOCFIT5 doses

ANOVA9 doses

2 4 6 8

Dopt9 doses

GADA9 doses

2 4 6 8

MCPMod9 doses

MTT9 doses

2 4 6 8

BMA9 doses

0

10

20

30

40

50

LOCFIT9 doses

Dose selected

% T

ria

ls

Emax, N = 250

Discussion

• With exception of the logistic response profile our dose-selection criterion misses (usually stops short of) the dose with highest PoS.

• Similar distributions have been observed regardless of the method used, or the number of doses studied.

1. Introduction

2. Design/Methods

3. Results/Discussion

4. Conclusions

Conclusions

• Methods with response-adaptive randomization component, particularly GADA, consistently outperform other designs on the overall PoS

• Only a small gain in the Phase III PoS is observed if the Phase II sample size is increased from 150 to 250

Conclusions

• Design with smaller number of doses performed better

• The overall PoS for a design with two active doses is consistently much higher than that of a design with one active dose

Conclusions

• Increasing the sample size generally results in an improved PoS.

• Increasing the sample size also results in the increased costs. It is therefore important to study when and by how much to increase investments in the program.

Conclusions

• Our current dose-selection criteria (focused on MED) usually fails to detect the optimal dose for the Phase III• Future research to include different dose

selection approaches, including approaches based on the utility (safety + efficacy) criterion.