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March 2018

Case studies with mrgsolve: PBPK and QSP model implementation and utilization in R

March 24 @ 1:30 pm - 5:30 pm
UF School of Pharmacy, 6550 Sanger Road
Orlando, FL 32827 United States
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In this tutorial session, we will review case studies in PBPK and QSP modeling and simulation using mrgsolve in R.  mrgsolve (https://mrgsolve.github.io) is a free, open-source modeling and simulation platform to support ODE-based model development in R. Outline: mrgsolve overview (brief tutorial) PBPK model characterizing drug-drug interactions between HMG-CoA reductase inhibitors and cyclosporine (Yoshikado et al. 2016; PMID 27170342) Sensitivity analyses Parameter estimation Evaluation of combination chemotherapy regimens using a QSP model for MAP kinase signaling in colorectal cancer (Kirouac…

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May 2018

Advanced Use of Stan, rstan, and Torsten for Pharmacometric Applications

May 29 @ 8:30 am - 4:30 pm

Join us for a guided hands-on experience in the advanced use of Stan, rstan, and Torsten for Bayesian PKPD modeling.
Topics include: model evaluation and comparison, models with systems of ODEs, optimizing Stan code, using MCMC results for population and trial simulations, and much more!
You will execute Bayesian data analysis examples using Stan. Via the examples, you will learn to implement population PKPD models including those involving censoring, numerical solution of ODEs, and user-defined probability distributions and likelihoods.

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June 2018

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

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

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.

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