Next Article in Journal
Neuroimmunomodulatory Properties of Flavonoids and Derivates: A Potential Action as Adjuvants for the Treatment of Glioblastoma
Next Article in Special Issue
Population Pharmacokinetics of Amikacin in Patients on Veno-Arterial Extracorporeal Membrane Oxygenation
Previous Article in Journal
Elovanoids Counteract Inflammatory Signaling, Autophagy, Endoplasmic Reticulum Stress, and Senescence Gene Programming in Human Nasal Epithelial Cells Exposed to Allergens
Previous Article in Special Issue
Variability of Tacrolimus Trough Concentration in Liver Transplant Patients: Which Role of Inflammation?
Article

Implementation and Comparison of Two Pharmacometric Tools for Model-Based Therapeutic Drug Monitoring and Precision Dosing of Daptomycin

1
Hospices Civils de Lyon, Groupement Hospitalier Nord, Service de Pharmacie, Hôpital Pierre Garraud, Service Pharmaceutique, 136 Rue du Commandant Charcot, 69005 Lyon, France
2
School of Management and Engineering Vaud (HEIG-VD), HES-SO University of Applied Sciences and Arts Western Switzerland, 1400 Yverdon-les-Bains, Switzerland
3
Hôpital Nord-Ouest, Service de Médecine Interne et des Maladies Infectieuses, 69400 Villefranche sur Saône, France
4
Hospices Civils de Lyon, Groupement Hospitalier Sud, Service de Biochimie et Biologie Moléculaire, UM Pharmacologie-Toxicologie, 69310 Pierre-Bénite, France
5
Hospices Civils de Lyon, Groupement Hospitalier Nord, Hôpital de la Croix-Rousse, Service des Maladies Infectieuses et Tropicales, Centre Interrégional de Référence pour la Prise en Charge des Infections Ostéo-Articulaires Complexes (CRIOAc Lyon), 69004 Lyon, France
6
ISPB—Facultés de Médecine et de Pharmacie de Lyon, Université Lyon 1, University of Lyon, 69008 Lyon, France
7
CIRI—Centre International de Recherche en Infectiologie, Inserm, U1111, Université Claude Bernard Lyon 1, CNRS, UMR5308, Ecole Normale Supérieure de Lyon, University of Lyon, 69007 Lyon, France
8
Laboratoire de Biométrie et Biologie Evolutive, UMR CNRS 5558, Université Lyon 1, University of Lyon, 69100 Villeurbanne, France
*
Author to whom correspondence should be addressed.
Academic Editors: Zoubir Djerada and Xavier Delavenne
Pharmaceutics 2022, 14(1), 114; https://doi.org/10.3390/pharmaceutics14010114
Received: 15 November 2021 / Revised: 22 December 2021 / Accepted: 23 December 2021 / Published: 4 January 2022
(This article belongs to the Special Issue Innovative Tools for Therapeutic Drug Monitoring)
Daptomycin is a candidate for therapeutic drug monitoring (TDM). The objectives of this work were to implement and compare two pharmacometric tools for daptomycin TDM and precision dosing. A nonparametric population PK model developed from patients with bone and joint infection was implemented into the BestDose software. A published parametric model was imported into Tucuxi. We compared the performance of the two models in a validation dataset based on mean error (ME) and mean absolute percent error (MAPE) of individual predictions, estimated exposure and predicted doses necessary to achieve daptomycin efficacy and safety PK/PD targets. The BestDose model described the data very well in the learning dataset. In the validation dataset (94 patients, 264 concentrations), 21.3% of patients were underexposed (AUC24h < 666 mg.h/L) and 31.9% of patients were overexposed (Cmin > 24.3 mg/L) on the first TDM occasion. The BestDose model performed slightly better than the model in Tucuxi (ME = −0.13 ± 5.16 vs. −1.90 ± 6.99 mg/L, p < 0.001), but overall results were in agreement between the two models. A significant proportion of patients exhibited underexposure or overexposure to daptomycin after the initial dosage, which supports TDM. The two models may be useful for model-informed precision dosing. View Full-Text
Keywords: daptomycin; pharmacokinetics; therapeutic drug monitoring; model-informed precision dosing; bone and joint infection daptomycin; pharmacokinetics; therapeutic drug monitoring; model-informed precision dosing; bone and joint infection
Show Figures

Figure 1

MDPI and ACS Style

Heitzmann, J.; Thoma, Y.; Bricca, R.; Gagnieu, M.-C.; Leclerc, V.; Roux, S.; Conrad, A.; Ferry, T.; Goutelle, S. Implementation and Comparison of Two Pharmacometric Tools for Model-Based Therapeutic Drug Monitoring and Precision Dosing of Daptomycin. Pharmaceutics 2022, 14, 114. https://doi.org/10.3390/pharmaceutics14010114

AMA Style

Heitzmann J, Thoma Y, Bricca R, Gagnieu M-C, Leclerc V, Roux S, Conrad A, Ferry T, Goutelle S. Implementation and Comparison of Two Pharmacometric Tools for Model-Based Therapeutic Drug Monitoring and Precision Dosing of Daptomycin. Pharmaceutics. 2022; 14(1):114. https://doi.org/10.3390/pharmaceutics14010114

Chicago/Turabian Style

Heitzmann, Justine, Yann Thoma, Romain Bricca, Marie-Claude Gagnieu, Vincent Leclerc, Sandrine Roux, Anne Conrad, Tristan Ferry, and Sylvain Goutelle. 2022. "Implementation and Comparison of Two Pharmacometric Tools for Model-Based Therapeutic Drug Monitoring and Precision Dosing of Daptomycin" Pharmaceutics 14, no. 1: 114. https://doi.org/10.3390/pharmaceutics14010114

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop