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A PK & PBPK Modeling Workflow in R: Simulation, Optimization & Visualization

October 9, 2020 @ 11:00 am - 3:00 pm

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After a brief introduction to mrgsolve (https://mrgsolve.github.io), we will discuss concepts and applications for using the package in R to simulate from pharmacokinetic (PK) and physiologically-based PK (PBPK) models, estimate parameters given a model and data, and visualize simulation results with a Shiny app. We will establish a basic framework for running optimization in R and work hands-on examples using different optimizers, including local and global search algorithms. Building on this framework, we will also illustrate related workflows including global and local sensitivity analysis. Finally, we will develop and deploy a Shiny app using Rstudio Connect, allowing interaction with the model and optimization results by non-modeling stakeholders.


Kyle T. Baron, Pharm.D., Ph.D.
Principal Scientist I, Metrum Research Group
Kyle joined MetrumRG in 2010 after receiving his Pharm.D. and Ph.D. in Experimental and Clinical Pharmacology from the University of Minnesota. As a member of our translational and systems pharmacology group, Kyle has worked to support sponsor development programs in a variety of therapeutic areas, including chronic hepatitis C infection, HIV, calcium homeostasis and bone health, type-2 diabetes, and cystic fibrosis. Kyle is the developer and maintainer of mrgsolve (https://mrgsolve.github.io) and also leads workshops at all levels to guide other M&S scientists in the effective use of this simulation tool in PKPD, PBPK, and QSP modeling. Kyle also serves as adjunct faculty in Experimental and Clinical Pharmacology at the University of Minnesota.

Devin Pastoor, Ph.D.
Vice President, Technology Solutions, Metrum Research Group
Devin joined MetrumRG in 2018 as the Senior Director of Technology Solutions. Prior to joining MetrumRG, Devin spent 6 years working with companies to help make informed drug development decisions under uncertainty. Devin specializes in integrating advanced statistical methodologies and data pipelines with modern, open-source tools in cloud environments.