William R. Gillespie, Ph.D.

Senior Science Advisor, Fellow I

For over 20 years Bill has been involved in the development and application of pharmacometric methodology for enhancing drug treatment, development and regulation. His current interests include the use of Bayesian modeling and simulation to optimize decision-making in clinical drug development and treatment. He plans to make Bayesian modeling and simulation methods more accessible via training programs and development of software tools.

Recent publications by this scientist

bbr.bayes: An Open-Source Tool to Facilitate an Efficient, Reproducible Bayesian Workflow Using NONMEM

July 8, 2024

Presented at PAGE 2024. The bbr.bayes package reduces much of the friction associated with a Bayesian pharmacometrics analysis in NONMEM® and promotes good practice applications. 

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Model-based meta-analysis using latent variable modeling to set benchmarks for new treatments of systemic lupus erythematosus

December 11, 2023

Leveraging a sophisticated Bayesian framework and latent variable models, this research compared treatment effects against placebos, setting a new benchmark for assessing efficacy in SLE treatments. This novel MBMA not only benchmarks the efficacy of these compounds but also showcases the application of latent variable models in understanding chronic disease trajectories.

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Bayesian modeling workflow for pharmacometric applications using bbr.bayes with Stan/Torsten

June 27, 2023

Presented by Bill Gillespie at StanCon 2023, this workshop highlights how to leverage the R package bbr.bayes to create traceable and reproducible Bayesian modeling workflows. The current version of bbr.bayes supports Stan models using cmdstanr, and future releases will include support for Bayesian modeling with NONMEM.

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