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Development of a dosing algorithm for meropenem in critically ill patients based on a population pharmacokinetic/pharmacodynamic analysis

  • Effective antibiotic dosing is vital for therapeutic success in critically ill patients. This work aimed to develop an algorithm to identify appropriate meropenem dosing in critically ill patients. Population pharma-cokinetic (PK) modelling was performed in NONMEM (R) 7.3 based on densely sampled meropenem serum samples (n(patients) = 48; n(samples) =1376) and included a systematic analysis of 27 pre-selected covariates to identify factors influencing meropenem exposure. Using Monte Carlo simulations newly considering the uncertainty of PK parameter estimates, standard meropenem dosing was evaluated with respect to attainment of the pharmacokinetic/pharmacodynamic (PK/PD) target and was compared with alternative infusion regimens (short-term, prolonged, continuous; daily dose, 2000-6000 mg). Subsequently, a dosing algorithm was developed to identify appropriate dosing regimens. The two-compartment population PK model included three factors influencing meropenem pharmacokinetics: the Cockcroft-Gault creatinine clearance (CLCRCG ) onEffective antibiotic dosing is vital for therapeutic success in critically ill patients. This work aimed to develop an algorithm to identify appropriate meropenem dosing in critically ill patients. Population pharma-cokinetic (PK) modelling was performed in NONMEM (R) 7.3 based on densely sampled meropenem serum samples (n(patients) = 48; n(samples) =1376) and included a systematic analysis of 27 pre-selected covariates to identify factors influencing meropenem exposure. Using Monte Carlo simulations newly considering the uncertainty of PK parameter estimates, standard meropenem dosing was evaluated with respect to attainment of the pharmacokinetic/pharmacodynamic (PK/PD) target and was compared with alternative infusion regimens (short-term, prolonged, continuous; daily dose, 2000-6000 mg). Subsequently, a dosing algorithm was developed to identify appropriate dosing regimens. The two-compartment population PK model included three factors influencing meropenem pharmacokinetics: the Cockcroft-Gault creatinine clearance (CLCRCG ) on meropenem clearance; and body weight and albumin on the central and peripheral volume of distribution, respectively; of these, only CLCRCG was identified as a vital influencing factor on PK/PD target attainment. A three-level dosing algorithm was developed (considering PK parameter uncertainty), suggesting dosing regimens depending on renal function and the level (L) of knowledge about the infecting pathogen (L1, pathogen unknown; L2, pathogen known; L3((-MIC)), pathogen and susceptibility known; L3((+MIC)), MIC known). Whereas patients with higher CLCRCG and lower pathogen susceptibility required mainly intensified dosing regimens, lower than standard doses appeared sufficient for highly susceptible pathogens. In conclusion, a versatile meropenem dosing algorithm for critically ill patients is proposed, indicating appropriate dosing regimens based on patient- and pathogen-specific information. (C) 2019 Published by Elsevier B.V.show moreshow less

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Author details:Lisa EhmannGND, Michael ZollerGND, Iris K. MinichmayrGND, Christina ScharfORCiDGND, Wilhelm HuisingaORCiDGND, Johannes ZanderORCiD, Charlotte KloftORCiDGND
DOI:https://doi.org/10.1016/j.ijantimicag.2019.06.016
ISSN:0924-8579
ISSN:1872-7913
Pubmed ID:https://pubmed.ncbi.nlm.nih.gov/31229669
Title of parent work (English):International journal of antimicrobial agents
Publisher:Elsevier
Place of publishing:Amsterdam
Publication type:Article
Language:English
Date of first publication:2019/06/20
Publication year:2019
Release date:2020/11/16
Tag:Dosing algorithm; Intensive care; Pharmacokinetics/pharmacodynamics; Renal function; beta-Lactams
Volume:54
Issue:3
Number of pages:9
First page:309
Last Page:317
Funding institution:Merieux Research Grant (Institut Merieux, Lyon, France)
Organizational units:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Biochemie und Biologie
DDC classification:6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit
Peer review:Referiert
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