Parametric and nonparametric population pharmacokinetic models to assess probability of target attainment of imipenem concentrations in critically ill patients

Femke de Velde*, Brenda C.M. de Winter, Michael N. Neely, Jan Strojil, Walter M. Yamada, Stephan Harbarth, Angela Huttner, Teun van Gelder, Birgit C.P. Koch, Anouk E. Muller

*Corresponding author for this work

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Abstract

Population pharmacokinetic modeling and simulation (M&S) are used to improve antibiotic dosing. Little is known about the differences in parametric and nonparametric M&S. Our objectives were to compare (1) the external validation of parametric and nonparametric models of imipenem in critically ill patients and (2) the probability of target attainment (PTA) calculations using simulations of both models. The M&S software used was NONMEM 7.2 (parametric) and Pmetrics 1.5.2 (nonparametric). The external predictive performance of both models was adequate for eGFRs ≥ 78 mL/min but insufficient for lower eGFRs, indicating that the models (developed using a population with eGFR ≥ 60 mL/min) could not be extrapolated to lower eGFRs. Simulations were performed for three dosing regimens and three eGFRs (90, 120, 150 mL/min). Fifty percent of the PTA results were similar for both models, while for the other 50% the nonparametric model resulted in lower MICs. This was explained by a higher estimated between-subject variability of the nonparametric model. Simulations indicated that 1000 mg q6h is suitable to reach MICs of 2 mg/L for eGFRs of 90–120 mL/min. For MICs of 4 mg/L and for higher eGFRs, dosing recommendations are missing due to largely different PTA values per model. The consequences of the different modeling approaches in clinical practice should be further investigated.

Original languageEnglish
Article number2170
JournalPharmaceutics
Volume13
Issue number12
DOIs
Publication statusPublished - 16 Dec 2021

Bibliographical note

Funding Information:
Funding: This research was funded by the Innovative Medicines Initiative Joint Undertaking under grant agreement no. [115523], resources of which are composed of financial contribution from the European Union’s Seventh Framework Programme (FP7/2007–2013) and EFPIA companies’ in-kind contribution. The research leading to these results was conducted as part of the COMBACTE-NET consortium. For further information please refer to http://www.combacte.com/, accessed on 8 November 2021. The popPK models were developed using data of a cohort study funded by a Research and Development Grant awarded by the Geneva University Hospitals in 2009 [PRD 09-II-025]. AH was partially supported by the EU-funded project AIDA [grant Health-F3-2011-278348]. The external validation was performed using data of a study supported by the Internal Grant Agency of Palacky University (Olomouc, Czech Republic) [IGA UPOL2014 LF 008].

Funding Information:
Conflicts of Interest: F.d.V., B.C.M.d.W., M.N.N., J.S., A.H. and A.E.M. declare that they have no conflict of interest. B.K. has received research funding from ZonMw (Dutch governmental support) and Teva. S.H. has received honoraria from Sandoz for participation in a Scientific Advisory Board. T.v.G. has received honoraria as consultant/speaker from Aurinia Pharma, Vitaeris, Roche Diagnostics, Novartis, Astellas, and Chiesi, and grant support for transplant related studies from Chiesi and Astellas. None of the EFPIA partners involved in the COMBACTE-NET consortium have a conflict of interest; none of them contributed to this article.

Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.

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