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Simulation from ODE-based population PK/PD and systems pharmacology models in R using mrgsolve

June 2 @ 8:30 am - 4:30 pm

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Montreux, Switzerland (PAGE satellite meeting, Eurotel – Club Salon, 1820 Montreux)

Instructors: Matthew Riggs, Ph.D. and Kyle Baron, Pharm.D., Ph.D.

Workshop summary: We will provide a guided hands-on experience in the use of the R package mrgsolve. mrgsolve is a free, open source, validated R package to facilitate simulation from hierarchical, ODE-based PK/PD and systems pharmacology models frequently employed in pharmaceutical research and development programs. You will code, execute, and summarize PK, PK/PD and systems pharmacology model simulations using mrgsolve and R.  Through many examples, you will learn to implement model-based simulations to help address questions at a variety of stages of a development program.

Full Price: $600
Academia/government attendees: $300
Students: $150

Materials Provided by Metrum: Metworx user login (with 1-week access post-workshop), course slides, data and code for all examples.  

Requirements for Attendees: Knowledge and experience in PKPD modeling and simulation, nonlinear mixed effects modeling and the use of R (or S-PLUS).  

Participants should bring a laptop that meets the following requirements:
Browser: Chrome, Firefox, or Safari
– Internet access via Wi-Fi

Upon completion of this workshop, participants should be able to:

  • Code ODE-based models in mrgsolve format 

  • Work with mrgsolve model objects and simulation output 

  • Create simulations of varying complexity, including sensitivity analyses, using event objects and simulation data sets 

  • Create population simulations that incorporate uncertainty in the parameters to address questions in drug development 

Course Outline:

  • Assign login credentials and check out course materials
  • Hands-on Introduction to mrgsolve (morning coffee break included) 

    • Installation overview
      • Where to get mrgsolve
    • Basic introduction to mrgsolve
      • Code a very basic model
      • Load and work with model object
      • Simulation with event objects and data sets
      • Handling simulated output
    • Models with covariates and population elements
    • Updating the model object and sensitivity analyses
  • Lunch
  • Applied simulation with PK/PD, PBPK, and QSP models (afternoon coffee break included) 

    • Simulation from a population model with and without uncertainty in the parameters using a PK/PD model for Fc-OPG in postmenopausal women
    • Probability of technical success assessment using EPO PK/PD model
    • Evaluate combination chemotherapy regimens with a QSP model characterizing MAP kinase signalling in colorectal cancer
    • Sensitivity analysis and parameter optimization in a PBPK model characterizing drug-drug interaction between HMG-CoA reductase inhibitors and cyclosporine
  • Discussion and summary