Session IX (May 17, 8:30am-10:00am): Optimal Experimental Design, organized by Abhyuday Mandal
Title: Nature-inspired Metaheuristics for Designing Innovative Drug Studies
Speaker: Weng Kee Wong, UCLA
Abstract: Nature-inspired metaheuristics is widely used in computer science and engineering but seems greatly underused in pharmaceutical and clinical science research. This class of algorithms is appealing because they are essentially assumptions free, fast and have been shown that they are capable of tackling various types of high dimensional complex optimization problems. We briefly review some exemplary nature-inspired metaheuristic algorithms and show (i) how they can be applied to extend Simon’s 2 stage designs for a Phase II trial with a single alternative hypothesis to one with multiple alternative hypotheses to capture the uncertainty of the efficacy of the drug more accurately, and (ii), how to construct a global clinical trial that can attain the large enrollment target with high probability at minimum cost and subject to multiple linear or nonlinear constraints. We also indicate how metaheuristics can be applied to develop more realistic and flexible adaptive designs for early phase clinical trials.