Tony Pourmohamad

Tony Pourmohamad serves as both Principal Statistical Scientist in the Department of Data and Statistical Sciences at Genentech and Assistant Adjunct Professor in the Statistics Department at the University of California, Santa Cruz. His dual appointment bridges pharmaceutical industry applications with academic research in statistical methodology.

Dr. Pourmohamad's primary research interests focus on Bayesian statistical methods with applications in pharmaceutical dissolution testing and clinical/nonclinical biostatistics. His work specializes in Bayesian optimization, modeling of computer experiments, and developing statistical frameworks for pharmaceutical equivalence testing. He has made significant contributions through his R packages that implement novel Bayesian approaches for dissolution profile analysis.

His publication record demonstrates expertise at the intersection of pharmaceutical statistics and Bayesian methodology, particularly in dissolution testing applications. The research shows a clear trajectory from his doctoral work on constrained optimization for computer experiments to current industry applications in biostatistics.

As an active developer, he maintains several R packages including BayesDissolution for Bayesian dissolution modeling and bmet for multigroup equivalence testing, reflecting his commitment to translating statistical research into practical tools for the pharmaceutical industry.