NONMEM is a
non-linear mixed-effects modeling software package developed by Stuart L. Beal and Lewis B. Sheiner in the late 1970s at
University of California, San Francisco
The University of California, San Francisco (UCSF) is a public land-grant research university in San Francisco, California. It is part of the University of California system and is dedicated entirely to health science and life science. It con ...
, and expanded by Robert Bauer at Icon PLC. Its name is an acronym for NON-linear
mixed effects modeling but it is especially powerful in the context of
population pharmacokinetics,
pharmacometrics, and
PK/PD models PK/PD modeling (pharmacokinetic/pharmacodynamic modeling) (alternatively abbreviated as PKPD or PK-PD modeling) is a technique that combines the two classical pharmacologic disciplines of pharmacokinetics and pharmacodynamics. It integrates a pharm ...
.
NONMEM models are written in NMTRAN, a dedicated
model specification language that is translated into
FORTRAN, compiled on the fly and executed by a command-line script. Results are presented as text output files including tables.
There are multiple interfaces to assist modelers with housekeeping of files, tracking of model development, goodness-of-fit evaluations and graphical output, such as PsN and xpose and Wings for NONMEM.
Current version for NONMEM is 7.5.
Model estimation
NONMEM estimates its models according to principles of
maximum likelihood estimation
In statistics, maximum likelihood estimation (MLE) is a method of estimating the parameters of an assumed probability distribution, given some observed data. This is achieved by maximizing a likelihood function so that, under the assumed stati ...
.
nonlinear mixed-effects model
Nonlinear mixed-effects models constitute a class of statistical models generalizing mixed model, linear mixed-effects models. Like linear mixed-effects models, they are particularly useful in settings where there are multiple measurements within t ...
generally do not have close-formed solutions, and therefore specific estimation methods are applied, such as linearization methods as first-order (FO), first-order conditional (FOCE) or the laplacian (LAPL), approximation methods such as iterative-two stage (ITS), importance sampling (IMP), stochastic approximation estimation (SAEM) or direct sampling.
References
External links
Product site
Numerical software
Pharmacodynamics
Pharmacokinetics
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