PopED - Population (and Individual) Optimal Experimental Design
Optimal experimental designs for both population and individual studies based on nonlinear mixed-effect models. Often this is based on a computation of the Fisher Information Matrix. This package was developed for pharmacometric problems, and examples and predefined models are available for these types of systems. The methods are described in Nyberg et al. (2012) <doi:10.1016/j.cmpb.2012.05.005>, and Foracchia et al. (2004) <doi:10.1016/S0169-2607(03)00073-7>.
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nlmeoptimal-designpharmacodynamicspharmacokineticspharmacometricspkpdpopulationpopulation-model
9.65 score 33 stars 1 dependents 353 scripts 378 downloadsxpose4 - Diagnostics for Nonlinear Mixed-Effect Models
A model building aid for nonlinear mixed-effects (population) model analysis using NONMEM, facilitating data set checkout, exploration and visualization, model diagnostics, candidate covariate identification and model comparison. The methods are described in Keizer et al. (2013) <doi:10.1038/psp.2013.24>, and Jonsson et al. (1999) <doi:10.1016/s0169-2607(98)00067-4>.
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diagnosticsnonmempharmacometricspopulation-modelxpose
7.33 score 38 stars 314 scripts 820 downloadsncappc - NCA Calculations and Population Model Diagnosis
A flexible tool that can perform (i) traditional non-compartmental analysis (NCA) and (ii) Simulation-based posterior predictive checks for population pharmacokinetic (PK) and/or pharmacodynamic (PKPD) models using NCA metrics. The methods are described in Acharya et al. (2016) <doi:10.1016/j.cmpb.2016.01.013>.
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5.64 score 17 stars 17 scripts 306 downloads