Join us *TOMORROW AT NOON (EDT)* to learn how to use mrgsolve to facilitate
simulation from hierarchical, ODE‐based PK/PD and systems pharmacol=
models frequently employed in pharmaceutical R&D programs.
With mrgsolve, you are able to implement model‐based simulations to=
address questions at a variety of stages of a development program. This
presentation is a part of the ISoP Pharmacometrics Study Group.
*Live link: *http://www.youtube.com/watch?v=ts3Lj3hVyiw
mrgsolve facilitates simulation in R from hierarchical, ordinary
differential equation (ODE) based models typically employed in drug
development. The modeler creates a model specification file consisting of R
and C++ code that is parsed, compiled, and dynamically loaded into the R
session. Input data are passed in and simulated data are returned as R
objects, so disk access is never required during the simulation cycle after
- NMTRAN-like input data sets
- Bolus, infusion, compartment on/off and reset functionality
- Bioavailability, ALAG, SS, II, ADDL, MTIME
- Multivariate normal random effects simulated using RcppArmadillo
- Compatible with parameter estimation and design packages in R (nlme,
saemix, PopED, PFIM)
- Integration with data summary (dplyr) and plotting (ggplot, lattice)
- Parallelization with existing R infrastructure (mclapply) or Sun Grid
- Compatible with output from many different model estimation platforms
- Easily integrated with Shiny to create model-visualization applications
mrgsolve is a powerful and efficient tool for simulation from ODE-based
PK/PD and systems pharmacology models. The resulting computational
efficiency facilitates model exploration and application, both during model
development and decision-making phases of a drug development program.
User Guide: https://mrgsolve.github.io/user_guide
About the StudyGroup: https://isop-phmx.github.io/studyGroup/
We are also offering hands-on mrgsolve workshops in a city near you! Visit
for more info.
Hope you can join us!
Metrum Research Group Team
Received on Thu May 12 2016 - 16:14:54 EDT