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Volume 14
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Article

Population Pharmacokinetic/Pharmacodynamic Modelling of Daptomycin for Schedule Optimization in Patients with Renal Impairment

by
Teresa García-Martínez
1,2,
María Dolores Bellés-Medall
2,
Maria García-Cremades
3,
Raúl Ferrando-Piqueres
2,
Victor Mangas-Sanjuán
1,4,* and
Matilde Merino-Sanjuan
1,4
1
Department of Pharmacy and Pharmaceutical Technology and Parasitology, University of Valencia, 46100 Valencia, Spain
2
Department of Pharmacy, University Hospital of Castellon, 12004 Castellon, Spain
3
Department of Pharmaceutics and Food Technology, School of Pharmacy, Complutense University of Madrid, 28040 Madrid, Spain
4
Interuniversity Research Institute for Molecular Recognition and Technological Development, 46022 Valencia, Spain
*
Author to whom correspondence should be addressed.
Pharmaceutics 2022, 14(10), 2226; https://doi.org/10.3390/pharmaceutics14102226
Submission received: 26 August 2022 / Revised: 14 October 2022 / Accepted: 15 October 2022 / Published: 18 October 2022
(This article belongs to the Special Issue The Role of Pharmacometrics in Drug Discovery and Development Process (Volume II))
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Abstract

The aims of this study are (i) to develop a population pharmacokinetic/pharmacodynamic model of daptomycin in patients with normal and impaired renal function, and (ii) to establish the optimal dose recommendation of daptomycin in clinical practice. Several structural PK models including linear and non-linear binding kinetics were evaluated. Monte Carlo simulations were conducted with a fixed combination of creatinine clearance (30–90 mL/min/1.73 m2) and body weight (50–100 kg). The final dataset included 46 patients and 157 daptomycin observations. A two-compartment model with first-order peripheral distribution and elimination kinetics assuming non-linear protein-binding kinetics was selected. The bactericidal effect for Gram+ strains with MIC ≤ 0.5 mg/L could be achieved with 5–12 mg/kg daily daptomycin based on body weight and renal function. The administration of 10–17 mg/kg q48 h daptomycin allows to achieve bactericidal effect for Gram+ strains with MIC ≤ 1 mg/L. Four PK samples were selected as the optimal sampling strategy for an accurate AUC estimation. A quantitative framework has served to characterize the non-linear binding kinetics of daptomycin in patients with normal and impaired renal function. The impact of different dosing regimens on the efficacy and safety outcomes of daptomycin treatment based on the unbound exposure of daptomycin and individual patient characteristics has been evaluated.
Keywords: daptomycin; pharmacokinetic; AUC; optimal dose selection; creatinine clearance daptomycin; pharmacokinetic; AUC; optimal dose selection; creatinine clearance

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MDPI and ACS Style

García-Martínez, T.; Bellés-Medall, M.D.; García-Cremades, M.; Ferrando-Piqueres, R.; Mangas-Sanjuán, V.; Merino-Sanjuan, M. Population Pharmacokinetic/Pharmacodynamic Modelling of Daptomycin for Schedule Optimization in Patients with Renal Impairment. Pharmaceutics 2022, 14, 2226. https://doi.org/10.3390/pharmaceutics14102226

AMA Style

García-Martínez T, Bellés-Medall MD, García-Cremades M, Ferrando-Piqueres R, Mangas-Sanjuán V, Merino-Sanjuan M. Population Pharmacokinetic/Pharmacodynamic Modelling of Daptomycin for Schedule Optimization in Patients with Renal Impairment. Pharmaceutics. 2022; 14(10):2226. https://doi.org/10.3390/pharmaceutics14102226

Chicago/Turabian Style

García-Martínez, Teresa, María Dolores Bellés-Medall, Maria García-Cremades, Raúl Ferrando-Piqueres, Victor Mangas-Sanjuán, and Matilde Merino-Sanjuan. 2022. "Population Pharmacokinetic/Pharmacodynamic Modelling of Daptomycin for Schedule Optimization in Patients with Renal Impairment" Pharmaceutics 14, no. 10: 2226. https://doi.org/10.3390/pharmaceutics14102226

APA Style

García-Martínez, T., Bellés-Medall, M. D., García-Cremades, M., Ferrando-Piqueres, R., Mangas-Sanjuán, V., & Merino-Sanjuan, M. (2022). Population Pharmacokinetic/Pharmacodynamic Modelling of Daptomycin for Schedule Optimization in Patients with Renal Impairment. Pharmaceutics, 14(10), 2226. https://doi.org/10.3390/pharmaceutics14102226

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