Making Development Decisions that Maximize the Value of Your Por;olio Zoran Antonijevic Overview
•  IntroducAon •  Assessing the Value of a PharmaceuAcal Product/Por;olio •  Case Study I: Impact of Design on the Expected Value of a Product •  Case Study II: Oncology Por;olio OpAmizaAon •  Case Study III: Use of UAlity FuncAons for Program OpAmizaAon IntroducAon Introduction
What is the objecAve of opAmizaAon in drug development? •  Maximizing the value for a paAent •  Maximizing the value for a sponsor/investor OpAmizaAon can based on: -­‐  Individual or a group specific values (e.g., uAlity) -­‐  An objecAve parameter (e.g., NPV) Quantitative Utility
•  Bernoulli (1738); quanAtaAve uAlity –  UAlity funcAon, moral expecta7ons, or be:ng preferences Applica7ons in Drug Development •  MulAple development opAons can be compared based on the expected uAlity •  Dose selecAon •  MulAple stakeholders; potenAal uAlity funcAons: – 
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PaAent’s Clinician’s Regulatory Commercial Assessing the Value of a PharmaceuAcal Product/Por;olio Assessing the Value of a
Pharmaceutical Product
•  Approaches presented here differenAate itself from current pracAces in that they recognize the impact of study design parameters on the product/por;olio value. •  Three key components: –  Cost –  Revenues –  Risk (or inversely PoS) •  Expected Net Present Value (eNPV) incorporates all three components Relationship Between Sample Size
and eNPV
600 500 eNPV 400 300 200 100 0 Sample Size Quantification at the Portfolio Level
•  Budget limits set at the por;olio level –  Decisions interrelated •  ObjecAve to maximize profit at the por;olio level •  Design/Decision Parameters to be assessed at the por;olio level: –  PoC Decision Criteria –  FuAlity boundaries in Phase 3 studies –  OpAmal sample size in Phases 2 and 3 Case Study I: Impact of Design on the Expected Value of a Product Objectives
To assess the impact of Phase 2 design characterisAcs on the PoS in phase III and on the expected NPV of the product. The following phase II characterisAcs were studied: 1)  The staAsAcal approach to dose selecAon; 2)  The sample size used in Phase 2; 3)  The number of doses studied in Phase 2; and 4)  The number of doses selected to advance into Phase 3 Expected NPV
1 dose
2 doses, fast
600
800
2 doses, normal
1000
600
800
N = 250
logistic
N = 250
quadratic
N = 250
linear
N = 250
emax
N = 150
logistic
N = 150
quadratic
N = 150
linear
N = 150
emax
1000
LOCFIT
BMA
MTT
MCPMod
GADA
Dopt
ANOVA
LOCFIT
BMA
MTT
MCPMod
GADA
Dopt
ANOVA
600
800
1000
600
800
Average NPV (millions)
1000
12 Case Study II: Oncology Por;olio OpAmizaAon Objectives
•  OpAmize selecAon of projects to advance into Phase 3 given budget constraints •  Assess the impact of PoC sample sizes •  Op7mize sample size in Phase 3 studies under budget constraints, using the simula7on approach. Overview
Protocols T1: Cancer Type I A1 T2: Cancer Type II T3: Cancer Type III A2 A3 A4 A5 T1: Cancer Type I T2: Cancer Type II T1: Cancer Type I T2: Cancer Type II T1: Cancer Type I T2: Cancer Type II T1: Cancer Type I How to Allocate Sample Size in Phase 3?
•  Strategy 1: Determine sample size for each trial and calculate POS and NPV; do a naive selecAon among trials with highest eNPV to fit within budget limits. •  Strategy 2: Start all trials with sample size=0. Compare trials for the benefit gained from an incremental increase in sample size; increase the sample size for the best trial. Repeat this procedure unAl the budget limit is met. Conclusions
Study design has a major impact on the expected value of a pharmaceuAcal product/por;olio: –  Trial level: adapAve design. Early stopping for efficacy/
fuAlity, interim increase in power, populaAon enrichment* –  Program level. More effecAve dose-­‐finding can lead to higher success rates in Phase III and an improved efficacy/
safety profile –  PorColio level. Improved allocaAon of a fixed budget into individual trials. Conclusions
•  Joint input by R&D and commercial groups necessary •  Note: Cytel has developed a pracAcal decision support tool for integraAng trial design into the por;olio opAmizaAon process. Thank you. QuesAons / Comments? Zoran Antonijevic Back-­‐up Slides Case Study III: Use of UAlity FuncAons for Program OpAmizaAon True eNPV from
Distribution of Dose Selected in Phase 2
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Green: 300 fixed Blue: 300 adapAve Black: 600 fixed Red: 600 adapAve Theoretical Utility of Each of 5 Doses
Doses: lowest to highest: •  Red •  Black •  Green •  Cyan •  Blue Theoretical eNPV in $bn for
Each of Five Doses
Doses: lowest to highest: •  Red •  Black •  Green •  Cyan •  Blue Selection Frequencies in Phase 2