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An Approximation Approach for Response Adaptive Clinical Trial Design

Vishal Ahuja
W3 D122, UH

Multi-armed bandit (MAB) problems, typically modeled as Markov decision processes (MDPs), exemplify the exploration vs. exploitation tradeoff. An area that has motivated theoretical research in MAB designs is the study of clinical trials, where the application of such designs has the potential to significantly improve patient outcomes and reduce time-to-market. However, such designs have limited real-world application because of computational barriers that render exact approaches to solving MDPs impractical. We discuss the how adaptive designs can revolutionize clinical trials and present a novel approximation approach that allow for a computationally efficient implementation. We demonstrate the strength of our proposed approach through a retrospective implementation on a recently conducted phase 3 clinical trial.


Vishal Ahuja is an assistant professor at the Cox School of Business, Southern Methodist University. He also holds an appointment as an adjunct assistant professor of clinical sciences at the University of Texas Southwestern Medical Center. His research focuses on developing decision analytic tools that can be implemented easily by healthcare professionals and policymakers to improve patient health, advance the quality of care, and enhance the efficiency of delivery of care. A focus of Vishal’s research is chronic diseases, diabetes in particular, where he uses data analytics to improve patient outcomes. For his research, Vishal partners with health organizations such as the Dept. of Veterans Affairs, Parkland Hospital, and Baylor Heart Hospital. To bring relevance to his research, Vishal attempts to draw from his diverse work experience of over 7 years in the corporate sector that includes engineering and managerial roles in the chemical, manufacturing and consumer goods industry.