This hands-on workshop will provide participants with a technical foundation for physiologically-based pharmacokinetic (PBPK) model development in R using mrgsolve, a free, open-source modeling and simulation platform for ODE-based model development in R (https://mrgsolve.github.io).  The workshop gets started with an introduction to simulation with mrgsolve.  We’ll cover the essentials of a tidy simulation workflow in R. Then we’ll jump into PBPK modeling with mrgsolve.  After a brief introduction to principles of PBPK, we’ll work through case studies using PBPK modeling. The case studies use published models focused on problems like drug-drug interactions and exploring pharmacokinetics in special populations.  Finally, we will introduce tools and workflows in R to help you accomplish modeling tasks such as sensitivity analysis and parameter estimation.

October 11-12, 2017 (1.5 day ACoP9 satellite workshop)

Course Instructors: Ahmed Elmokadem, Ph.D. and Kyle Baron, Pharm.D., Ph.D.

Topic outline of Workshop:

• PBPK concepts
  • Why PBPK?
  • Types of PBPK models (flow-limited and permeability-limited)
  • Development of model equations
  • Databases for PBPK model parameters
• Introduction to mrgsolve for PBPK modeling
  • A tidy PBPK model-based simulation workflow in R
  • Implement dosing events
  • Customize simulation output
  • Approaches to sensitivity analysis with mrgsolve
  • Model specification basics
• Case studies in PBPK modeling
  • Statin/cyclosporine DDI model (Yoshikado et al. 2016, PMID 27170342)
  • Pediatric voriconazole PBPK model (Zane and Thakker 2014, PMID 25245942)
• PBPK modeling workflow in R
  • Sensitivity analyses
    • Exploratory simulation
    • Local sensitivity analysis
    • Global sensitivity analysis via sobol method
  • Parameter estimation
    • General optimization in R
    • Global search tools
• Discussion and wrap-up

Requirements for Attendees: Knowledge and experience in PK modeling and the use of R (or S-PLUS). Previous exposure to the mrgsolve simulation package (https://mrgsolve.github.io/) is helpful, but not required.  

Materials Provided by Sponsor: Course slides, data and code for all examples, online access for one week to a cloud-based compute server on which the software used in the course is installed.