Group Leader PKPD, Principal Scientist II
Curtis joined Metrum in 2014 after receiving his Pharm.D. from the University at Buffalo and completing a clinical PK/PD Fellowship through UNC Chapel Hill/Quintiles. His clinical experience includes infectious disease (bacterial), oncology, and chronic liver disease (HCV and NASH). Curtis’s research interests include Bayesian methodology and the application of M&S to help inform drug development decisions.
December 6, 2024
Presented at ACoP 2024. SHAP analyis, an interpretable ML technique, was applied to PopPK models with two examples: saturable PK and causal dependence in covariates. This analysis yieled insights beyond forest plots and clairified differences in different types of forest plots typically presented.
December 6, 2024
Presented at ACoP 2024. In this analysis aimed to evaluate the ability to estimate robust population PD parameters and a landmark endpoint in different scenarios. In the primary workflow different levels of missing PK data were tested. Additionally, varying degrees of of individual-level and residual variability were tested. Finally, scenarios with smaller populations were tested. In all scenarios, PD parameters and endpoints could be estimated with adequate accuracy and precision.
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.