A mathematical model for maximizing the value of phase 3 drug development portfolios incorporating budget constraints and risk

• Published in: Statistics in medicine Vol. 32; no. 10; pp. 1763 - 1777
• Main Authors: Patel, Nitin R., Ankolekar, Suresh, Antonijevic, Zoran, Rajicic, Natasa
• Format: Journal Article
• Language: English
• Published: England Blackwell Publishing Ltd 10.05.2013; Wiley Subscription Services, Inc
• Subjects: Bayes Theorem; Bayesian analysis; Biostatistics; budget constraints; Budgets - statistics & numerical data; Clinical Trials, Phase III as Topic - economics; Clinical Trials, Phase III as Topic - statistics & numerical data; Decision analysis; Decision Support Techniques; Drug Discovery - economics; Drug Discovery - statistics & numerical data; Humans; Integer programming; Mathematical models; Models, Statistical; phase 3 portfolio optimization; portfolio re-optimization; R&D; Research & development; Risk; stochastic integer programming; Stochastic models; Stochastic Processes
• ISSN: 0277-6715; 1097-0258
• DOI: 10.1002/sim.5731

We describe a value‐driven approach to optimizing pharmaceutical portfolios. Our approach incorporates inputs from research and development and commercial functions by simultaneously addressing internal and external factors. This approach differentiates itself from current practices in that it recognizes the impact of study design parameters, sample size in particular, on the portfolio value. We develop an integer programming (IP) model as the basis for Bayesian decision analysis to optimize phase 3 development portfolios using expected net present value as the criterion. We show how this framework can be used to determine optimal sample sizes and trial schedules to maximize the value of a portfolio under budget constraints. We then illustrate the remarkable flexibility of the IP model to answer a variety of ‘what‐if’ questions that reflect situations that arise in practice. We extend the IP model to a stochastic IP model to incorporate uncertainty in the availability of drugs from earlier development phases for phase 3 development in the future. We show how to use stochastic IP to re‐optimize the portfolio development strategy over time as new information accumulates and budget changes occur. Copyright © 2013 John Wiley & Sons, Ltd.