Assessment of the nlmixr R package for population pharmacokinetic modeling: A metformin case study
Issued Date
2023-01-01
Resource Type
ISSN
03065251
eISSN
13652125
Scopus ID
2-s2.0-85136861872
Pubmed ID
35976674
Journal Title
British Journal of Clinical Pharmacology
Volume
89
Issue
1
Start Page
330
End Page
339
Rights Holder(s)
SCOPUS
Bibliographic Citation
British Journal of Clinical Pharmacology Vol.89 No.1 (2023) , 330-339
Suggested Citation
Mak W.Y., Ooi Q.X., Cruz C.V., Looi I., Yuen K.H., Standing J.F. Assessment of the nlmixr R package for population pharmacokinetic modeling: A metformin case study. British Journal of Clinical Pharmacology Vol.89 No.1 (2023) , 330-339. 339. doi:10.1111/bcp.15496 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/82237
Title
Assessment of the nlmixr R package for population pharmacokinetic modeling: A metformin case study
Author's Affiliation
Faculty of Tropical Medicine, Mahidol University
School of Pharmaceutical Sciences, Universiti Sains Malaysia
Pharmetheus AB
Hospital Pulau Pinang
Great Ormond Street Hospital for Children NHS Foundation Trust
UCL Great Ormond Street Institute of Child Health
National Institute of Health
Seberang Jaya Hospital
School of Pharmaceutical Sciences, Universiti Sains Malaysia
Pharmetheus AB
Hospital Pulau Pinang
Great Ormond Street Hospital for Children NHS Foundation Trust
UCL Great Ormond Street Institute of Child Health
National Institute of Health
Seberang Jaya Hospital
Other Contributor(s)
Abstract
Aim: nlmixr offers first-order conditional estimation (FOCE), FOCE with interaction (FOCEi) and stochastic approximation estimation-maximisation (SAEM) to fit nonlinear mixed-effect models (NLMEM). We modelled metformin's pharmacokinetic data using nlmixr and investigated SAEM and FOCEi's performance with respect to bias and precision of parameter estimates, and robustness to initial estimates. Method: Compartmental models were fitted. The final model was determined based on the objective function value and inspection of goodness-of-fit plots. The bias and precision of parameter estimates were compared between SAEM and FOCEi using stochastic simulations and estimations. For robustness, parameters were re-estimated as the initial estimates were perturbed 100 times and resultant changes evaluated. Results: The absorption kinetics of metformin depend significantly on food status. Under the fasted state, the first-order absorption into the central compartment was preceded by zero-order infusion into the depot compartment, whereas for the fed state, the absorption into the depot was instantaneous followed by first-order absorption from depot into the central compartment. The means of relative mean estimation error (rMEE) ((Formula presented.)) and rRMSE ((Formula presented.)) were 0.48 and 0.35, respectively. All parameter estimates given by SAEM appeared to be narrowly distributed and were close to the true value used for simulation. In contrast, the distribution of estimates from FOCEi were skewed and more biased. When initial estimates were perturbed, FOCEi estimates were more biased and imprecise. Discussion: nlmixr is reliable for NLMEM. SAEM was superior to FOCEi in terms of bias and precision, and more robust against initial estimate perturbations.