First CRAN release of nlmixr

The nlmixr team is very proud to announce the first CRAN release of nlmixr (https://cran.r-project.org/web/packages/nlmixr/), an open source package for population PK and PKPD modelling. nlmixr builds on the RxODE package for simulation of nonlinear mixed effect models using ordinary differential equations, by implementing parameter estimation algorithms like nlme and

Major public release of nlmixr

The nlmixr team is very proud to announce a major public release of nlmixr, an open source package for population PK and PKPD modelling. nlmixr builds on the RxODE package for simulation of nonlinear mixed effect models using ordinary differential equations, by implementing parameter estimation algorithms like nlme and SAEM

nlmixr in Cuba

Part of the nlmixr team had the wonderful opportunity in June 2017 to train the next generation of pharmacometricians in Cuba. Wenping Wang and Mirjam N. Trame spent one week together with the Pharmacometrics group of Prof. Leyanis Rodriguez Vera from the College of Pharmacy at the University of Havana, Cuba.

Posters at PAGE!

nlmixr was featured on two posters at the recent PAGE conference in Budapest, Hungary. In one, by Rik Schoemaker and colleagues, the nlmixr team show comparisons between the built-in nlme, SAEM and FOCE-interaction methods, demonstrating that the nlmixr SAEM method in particular performs similarly to NONMEM’s FOCE-interaction method. In the

Introducing nlmixr

There’s a distinct shortage of tools for performing effective pharmacometric data analysis. There’s NONMEM, the gold standard; there’s Monolix; and there’s Phoenix WinNonlin. All of these tools do a good enough job, but are united by two critical issues: first, they’re closed and proprietary, and second, they cost the equivalent of a