Nonlinear mixed-effects models are frequently used for pharmacokinetic data analysis, and they account for inter-subject variability in pharmacokinetic ...

Nonlinear mixed-effects models are being widely used in pharmacokinetics to study the pharmacological pro- cesses within the body after administration of a drug ...

Nonlinear mixed-effects modeling provides a good solution for modeling sparse datasets. Using population pharmacokinetics (popPK) data as an example.

The algorithms behind nonlinear mixed effects models are certainly more complex than any of the other model types examined, but the basic ideas behind ...

nlmixr is a free and open-source R package for fitting nonlinear pharmacokinetic (PK), pharmacodynamic (PD), joint PK-PD, and quantitative systems pharmacology ...

This project focuses on three types of models: non-compartmental analysis, nonlinear mixed-effects models, and physiologically-based pharmacokinetic models.

24 сент. 2020 г. · Non-linear mixed-effects (NLME) models are versatile tools for simultaneously modeling pharmacokinetics (PK) and quantifying inter-individual ... Introduction · Materials and Methods · Results · Discussion

Nonlinear mixed-effects models are being widely used in pharmacokinetics to study the pharmacological pro- cesses within the body after administration of a drug ...

A mixed-effects model is a statistical model that incorporates both fixed effects and random effects. Fixed effects are population parameters assumed to be the ...

13 февр. 2017 г. · Nonlinear mixed-effects models are frequently used for pharmacokinetic data analysis, and they account for inter-subject variability in ...