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Chinese Journal of Clinical Pharmacology and Therapeutics ›› 2023, Vol. 28 ›› Issue (5): 525-535.doi: 10.12092/j.issn.1009-2501.2023.05.006

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Comparison of calculation results of five population pharmacokinetic analysis tools

HUANG Zhiwei1, LI Yi2, XU Xiaoyong3, ZHANG Lei1, SHEN Yifeng1, LI Huafang1   

  1. 1 Clinical Research Center of Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200000, China; 2 Institute of Antibiotics, Huashan Hospital, Fudan University, Shanghai 200000, China; 3 Department of Pharmacy, Children's Hospital of Fudan University, Shanghai 200000, China
  • Received:2022-11-21 Revised:2023-03-01 Online:2023-05-26 Published:2023-06-08

Abstract:

AIM: To compare the results calculated by population pharmacokinetic analysis tools Phoenix NLME, Monolix, R nlmixr package and CPhaMAS cloud platform with the gold standard sofeware NONMEM. METHODS: Fifty sparse sampling data sets based on a one-compartment model and fifty dense sampling data sets based on a two-compartment model were simulated, and the above five analysis tools were used to calculate the population typical value, individual variability and individual pharmacokinetic parameters. RESULTS: The population typical value and individual variability calculated by CPhaMAS and Phoenix NLME had the highest matching degree with NONMEM, followed by nlmixr. Monolix had the lowest matching degree, but Monolix and nlmixr might be more robust. The correspondence between clearance and distribution volume was better than the absorption rate constant. Except the absorption rate constant calculated by Monolix and intercompartmental clearance calculated by nlmixr, the correlation coefficients of individual pharmacokinetic parameters calculated by all analytical tools were greater than 0.99. CONCLUSION: The results calculated by the above four population pharmacokinetic analysis tools are highly correlated with that of NONMEM.

Key words: population pharmacokinetics, NONMEM, compartmental model

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