Several methods have been presented in the literature for the management of a pharmaceutical portfolio, i.e. selecting which clinical studies should be conducted. We compare two existing approaches that use stochastic programming techniques and formulate the problem as a mixed integer linear programme (MILP). The first approach will be referred to as the ROV (real option valuation) approach since values are assigned to drug development programmes using methods for real option valuation. The second approach will be referred to as the PS (project scheduling) approach as this approach focusses on the scheduling of clinical studies and is formulated similarly to the resource constrained project scheduling problem. The ROV approach treats the value of a drug development programme as stochastic whereas the PS approach treats the trial outcomes as the stochastic component of the programme. As a consequence, the two approaches may select different portfolios. An advantage of the PS approach is that a schedule for when trials are to be conducted is provided as part of the optimal solution. This advantage comes at a much increased computational burden, however.

中文翻译：

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投资组合级决策的随机规划方法的比较。

文献中已经提出了几种方法来管理药物组合，即选择应进行的临床研究。我们比较了两种使用随机编程技术的现有方法，并将该问题表述为混合整数线性程序（MILP）。第一种方法将被称为ROV（实物期权估值）方法，因为使用实物期权估值方法将价值分配给了药物开发计划。第二种方法将被称为PS（项目调度）方法，因为该方法专注于临床研究的调度，并且与资源受限的项目调度问题类似地制定。ROV方法将药物开发计划的价值视为随机的，而PS方法将试验结果视为计划的随机组成部分。结果，这两种方法可能选择不同的投资组合。PS方法的优点是，提供了进行试验的时间表，作为最佳解决方案的一部分。但是，该优点带来了大大增加的计算负担。