Monte Carlo Simulation for Trial Design Tool

Suresh Ankolekar (), Cyrus Mehta (), Rajat Mukherjee, Sam Hsiao, Jennifer Smith and Tarek Haddad
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Suresh Ankolekar: Cytel Inc
Cyrus Mehta: Cytel Inc
Rajat Mukherjee: Cytel Inc
Sam Hsiao: Cytel Inc
Jennifer Smith: Sunesis Pharmaceuticals Inc
Tarek Haddad: Medtronic Inc

Chapter 80 in Principles and Practice of Clinical Trials, 2022, pp 1563-1585 from Springer

Abstract: Abstract Clinical trials often involve design issues with mathematically intractable complexity. Being part of multi-phase drug development programs, the trial designs need to incorporate prior information in terms of historical data from earlier phases and available knowledge about related trials. Some trials with inherent limits on data collection may need augmentation with simulated pseudo-data. For planning of interim looks, group sequential and adaptive trials require accurate timeline predictions of reaching clinical milestones involving complex set of operational and clinical models. In general, clinical trial design involves an interactive process involving interplay of models, data, assumptions, insights, and experiences to address specific design issues before and during the trial. This offers a rich context for simulation-centric modeling, the theme of this chapter. We will focus on practical considerations of applying simulation modeling tools and techniques to design and implementation of clinical trials. This will be achieved through two real-life case studies and relevant illustrative examples drawn from literature and our practical experience.

Keywords: Adaptive design; Bayesian discount; Sample-size re-estimation; Design simulation; Power prior; Discount function; O’Brien-Fleming efficacy (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/978-3-319-52636-2_251

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