Adaptive Design and Flexible Approval of Clinical Trials

Dose-finding clinical trials are among the most critical cornerstones of the healthcare system. In this broad research area, there are many decision making problems that are extremely challenging to address. However, a small improvement may result in significant benefits to the society. Dose-finding clinical trials are extremely expensive and require multiple time-consuming and complicated R&D phases. Despite all the costs and the long time these trials need to conclude (on average over ten years for each new drug/technology), only less than 15\% of these trials successfully end up in a new approved drug entering the market. This problem is even exacerbated for the drugs that target rare diseases, where the costs of testing subjects are higher, sampling budgets are more restricted by the number of available patients, and the chances of success and expected payoffs are at much lower levels. In this dissertation, we first propose a new information-based objective function to guide the adaptive dose allocation as a part of Phase II clinical studies for which we show its merit in small sampling budgets. Then, we redesign Phase II clinical trials with the goal of personalizing this process and to find different target doses with certain efficacy levels, for different groups of patients. Finally, we move on to the FDA aspect of the approval process, and analyze flexible approval policies that the FDA can apply to Phase III clinical trials. The motivation for this work is based on recent studies that suggest flexible approval process can incentivize the research and development of new drugs for rare diseases. We hope that the results of our research help the clinicians, pharmaceutical companies, and the FDA with better understanding the consequences of their decisions, while leading to potentially more effective treatment/dose specification for the patients who are in need of new drugs