Nonlinear Mixed Effects Modeling (NONMEM) is a type of population pharmacokinetics/pharmacodynamics (popPK/PD) analysis used in Clinical Pharmacology research. The population PK approach combined with pharmacodynamics modeling, allows integrated analysis, interpretation, and prediction of the drug’s safety, efficacy, dose-concentration relationship, and dosing strategy.
Population modeling and simulation can be conducted using a variety of software including S-Plus, R ,Phoenix WinNonLin ,SAS (PROC NLMIXED), MatLab and Phoenix NLME. One software commonly used for used for POP PK/PD modeling in clinical pharmacology research is NONMEM. This is a powerful tool, but with highly defined formats required, dataset creation can be a time-consuming process.
To increase efficiency as well as reduce the opportunities for errors, software developers and statistical programmers in Cytel’s Quantitative Pharmacology and Pharmacometrics group have developed an automated approach using SAS. The team identified key data components of NONMEM datasets and developed a standard structure for each. They also created standard rules with regards to handling and merging different type of covariates.
At a 2016 conference, the Cytel Quantitative Pharmacology and Pharmacometrics team presented a poster presentation illustrating the process and the efficiencies gained from the approach. To download the poster, click the button below.
Further Reading
Scrambled Data: A Population PK/PD programming solution
Pharmacometrics tools of the trade: 4 factors to consider
An efficient tool for model based meta-analysis
Learn more about Cytel's Quantitative Pharmacology and Pharmacometrics services here.
