Clinical Trials for New Drug Development: Optimal Investment and Application

Music City Center 

Phase III clinical trials are costly and involve enrolling and treating hundreds or thousands of patients at multiple sites. The time, cost, and economic value of a drug upon completion are uncertain. We address the problem of determining when and how many test sites to open and at what rate to recruit patients. We model the problem as a discrete-time, discounted dynamic program aimed at maximizing the expected net present value of a drug, considering trial costs, the likelihood of approval based on the drug's quality, and its subsequent expected revenue if approved. The optimal policy is characterized by thresholds for the number of patients enrolled over time, which indicate when additional test centers should be opened and how many patients to target. Using data from completed trials, we show that these thresholds are relevant for decision-making, especially for low- to moderate-valued drugs. We also extend the model to account for multiple interim analyses and demonstrate that optimizing clinical trial capacity and utilization adds significant value, in addition to the option value of stopping the trial early

pharmaceutical drug development

clinical trial

R&D project management

optimal investment 

Biopharmaceutical Section