A mathematical model for maximizing the value of phase 3 drug development portfolios incorporating budget constraints and risk
A mathematical model for maximizing the value of phase 3 drug development portfolios incorporating budget constraints and risk
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DOI：
10.1002/sim.5731
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发表时间：
2013-05-10
影响因子：
2
通讯作者：
Rajicic, Natasa
中科院分区：
文献类型：
--
作者：
Patel, Nitin R.;Ankolekar, Suresh;Rajicic, Natasa
我们描述了一种价值驱动的方法来优化药品投资组合。我们的方法通过同时处理内部和外部因素，将研发和商业职能的投入结合在一起。这种方法与目前的做法不同，因为它认识到研究设计参数，特别是样本量对投资组合价值的影响。我们开发了一个整数规划(IP)模型作为贝叶斯决策分析的基础，以预期净现值为标准来优化第三阶段开发投资组合。我们展示了如何使用这个框架来确定最优样本量和试验时间表，以在预算限制下最大化投资组合的价值。然后，我们说明了IP模型在回答反映实践中出现的情况的各种假设问题时具有非凡的灵活性。我们将IP模型扩展到随机IP模型，以纳入未来第三阶段开发的早期开发阶段药物可用性的不确定性。我们展示了如何使用随机IP来随着时间的推移重新优化投资组合开发策略，因为新的信息积累和预算变化发生了。版权所有(C)2013 John Wiley&Sons，Ltd.
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 (c) 2013 John Wiley & Sons, Ltd.