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Updated: Oct 10, 2025

Multiplex Therapeutic Drug Monitoring by Isotope-dilution HPLC-MS/MS of Antibiotics in Critical Illnesses
Published on: August 30, 2018
Cefepime Precision Dosing Tool: from Standard to Precise Dose Using Nonparametric Population Pharmacokinetics
Mohammad H Alshaer1,2, Sylvain Goutelle3,4,5, Barbara A Santevecchi2
1Infectious Disease Pharmacokinetics Lab, Emerging Pathogens Institute, University of Floridagrid.15276.37, Gainesville, Florida, USA.
Abstract:
Cefepime is the second most common cephalosporin used in U.S. hospitals. We aim to develop and validate a cefepime population pharmacokinetic (PK) model and integrate it into a precision dosing tool for implementation. Two data sets (680 patients) were used to build the cefepime PK model in Pmetrics, and three data sets (34 patients) were used for the validation. A separate application data set (115 patients) was used for the implementation and validation of a precision dosing tool. The model support points and covariates were used to generate the optimal initial dose (OID). Cefepime PK was described by a two-compartment model including weight and creatinine clearance (CrCl) as covariates. The median rate of elimination was 0.30 h-1 (adults) and 0.96 h-1 (children), the central volume of distribution was 13.85 L, and the rate of transfer from the central to the peripheral compartments was 1.22 h-1 and from the peripheral to the central compartments was 1.38 h-1. After integration in BestDose, the observed versus predicted cefepime concentration fit using the application data set was excellent (R2 > 0.98), and the median difference between what was observed and what BestDose predicted on a second occasion was 4%. For the OID, cefepime at a 0.5- to 1-g 4-h infusion every 8 to 24 h (q8 to 24 h) with a CrCl of <70 mL/min was needed to achieve a target range of free trough:MIC 1 to 4 at a MIC of 8 mg/L, while continuous infusion was needed for higher CrCl and weight values. In conclusion, we developed and validated a cefepime model for clinical application. The model was integrated in a precision dosing tool for implementation, and the median concentration prediction bias was 4%. The OID algorithm was provided.
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