This is a simulated dataset from the ACOP 2016 poster. All Datasets were simulated with the following methods.
A data frame with 7,920 rows and 14 columns
Siumlated Subject ID
Simulated Dependent Variable
Simulated log(Dependent Variable)
Missing DV data item
NONMEM Event ID
Individual Simulated Volume
Individual Vm constant
Individual Km constant
Single Dose Flag
Richly sampled profiles were simulated for 4 different dose levels (10, 30, 60 and 120 mg) of 30 subjects each as single dose (over 72h), multiple dose (4 daily doses), single and multiple dose combined, and steady state dosing, for a range of test models: 1- and 2-compartment disposition, with and without 1st order absorption, with either linear or Michaelis-Menten (MM) clearance(MM without steady state dosing). This provided a total of 42 test cases. All inter-individual variabilities (IIVs) were set at 30 were the same for all models. A similar set of models was previously used to compare NONMEM and Monolix4. Estimates of population parameters, standard errors for fixed-effect parameters, and run times were compared both for closed-form solutions and using ODEs. Additionally, a sparse data estimation situation was investigated where 500 datasets of 600 subjects each (150 per dose) were generated consisting of 4 random time point samples in 24 hours per subject, using a first-order absorption, 1-compartment disposition, linear elimination model.
Schoemaker R, Xiong Y, Wilkins J, Laveille C, Wang W. nlmixr: an open-source package for pharmacometric modelling in R. ACOP 2016
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