Senior Scientist II
Matthew joined Metrum in 2019 as a Research Scientist. He holds an M.A. in Statistics from Boston University. Prior to Metrum, he worked for a variety of startup technology companies where he applied Bayesian methodologies in predictive models based on remote sensing data. His ongoing interests include communicating and leveraging uncertainty from a Bayesian perspective in scalable modeling and simulation projects.
April 1, 2024
Presented at ASCPT Annual Meeting 2024. Discover the synergy between Machine Learning and classical approaches in covariate identification. Our scientist, Matthew Wiens, explored this vital topic at the pre-conference session ‘Empowering Clinical Pharmacologists and Translational Scientists Using Artificial Intelligence: Unlocking Potential with Cutting-Edge Use Cases.’
December 11, 2023
In this tutorial, the principles of Bayesian model development, assessment and prior selection are outlined. An example pharmacokinetic model is used to demonstrate the implementation of Bayesian modeling using the nonlinear mixed-effects modeling software NONMEM.
November 28, 2023
Exposure-response (E-R) modeling frequently relies on the use of exposure metrics that summarize drug concentrations over time. This research presents simulations to demonstrate that certain commonly used exposure metrics, including average concentration up to an event time, are likely to lead to causal confounding under the very conditions that motivate their use.