Objective: To determine the pharmacokinetics (PK) of vancomycin in Chinese infant patients using a population pharmacokinetic (PKK) approach in order to provide support for individualized vancomycin therapy.
Method: The data included 72 sets of steady-state peak and trough serum concentrations from 61 infants (0 - 1 years). PPK analysis was performed using the nonlinear mixed-effects modeling software. Inter- and intraindividual variability was estimated for the clearance and distribution volume of vancomycin. The potential effects of patient sex, postnatal age, postconceptional age, height, weight, body surface area, body mass index, alanine aminotransferase, aspartate aminotransferase, total protein, albumin, white blood cell count, serum creatinine, and concomitant medications on vancomycin PKs were explored.
Results: A one-compartment linear model with first-order elimination was used to describe the data. Weight and postnatal age had a significant influence on vancomycin clearance. The typical population parameter estimates of clearance and distribution volume were 0.46 L/h and 4.45 L, respectively. Goodness-of-fit plots and bootstrap outcomes confirmed the relatively good stability and prediction capability of the model.
Conclusion: This study initially established a vancomycin PPK model to estimate individual PK parameters in Chinese infant patients.
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http://dx.doi.org/10.5414/CP202827 | DOI Listing |
Clin Pharmacokinet
January 2025
Division of Medicines, Department of Pharmacy, Pharmacy Service, Hospital Clinic of Barcelona, Universitat de Barcelona, Barcelona, Spain.
Population pharmacokinetic (popPK) models are an essential tool when implementing therapeutic drug monitoring (TDM) and to overcome dosing challenges in neonates in clinical practice. Since vancomycin, gentamicin, and amikacin are among the most prescribed antibiotics for the neonatal population, we aimed to characterize the popPK models of these antibiotics and the covariates that may influence the pharmacokinetic parameters in neonates and infants with no previous pathologies. We searched the PubMed, Embase, Web of Science, and Scopus databases and the bibliographies of relevant articles from inception to the beginning of February 2024.
View Article and Find Full Text PDFAntibiotics (Basel)
December 2024
Clinical Pharmacology Group, Health Research Institute of Santiago de Compostela (IDIS), 15706 Santiago de Compostela, Spain.
The use of artificial intelligence (AI) and, in particular, machine learning (ML) techniques is growing rapidly in the healthcare field. Their application in pharmacokinetics is of potential interest due to the need to relate enormous amounts of data and to the more efficient development of new predictive dose models. The development of pharmacokinetic models based on these techniques simplifies the process, reduces time, and allows more factors to be considered than with classical methods, and is therefore of special interest in the pharmacokinetic monitoring of antibiotics.
View Article and Find Full Text PDFAntibiotics (Basel)
November 2024
I. Mechnikov Research Institute for Vaccines and Sera, Moscow 105064, Russia.
Background/objectives: Due to a narrow therapeutic window, side-effects, toxicities, and individual pharmacokinetics (PK) variability, WHO classifies vancomycin (VCM) as a "watch antibiotic" whose use should be monitored to improve clinical effectiveness. Availability and ease of use have made the immunoassay technique the basic tool for the therapeutic drug monitoring (TDM) of VCM concentrations.
Methods: The present study describes the development of a TDM tool for VCM based on anti-eremomycin (ERM) antibody enzyme-linked immunosorbent assay (ELISA).
Sci Rep
December 2024
Internal Medicine Department - Nephrology, Botucatu School of Medicine, University São Paulo State-UNESP, District of Rubiao Junior, Botucatu, Sao Paulo, Brazil.
The pharmacokinetics and pharmacodynamics (PK/PD) of vancomycin change during HD, increasing the risk of subtherapeutic concentrations. The aim of this study was to evaluate during and after the conventional and prolonged hemodialysis sessions to identify the possible risk of the patient remaining without adequate antimicrobial coverage during therapy. Randomized, non-blind clinical trial, including critically ill adults with septic AKI on conventional (4 h) and prolonged HD (6 and 10 h) and using vancomycin for at least 72 h.
View Article and Find Full Text PDFSci Rep
December 2024
Faculty of Materials Science and Engineering, K. N. Toosi University of Technology, Tehran, Iran.
This paper introduces an evidence-based, design-of-experiments (DoE) approach to analyze and optimize drug delivery systems, ensuring that release aligns with the therapeutic window of the medication. First, the effective factors and release data of the system are extracted from the literature and meta-analytically undergo regression modeling. Then, the interaction and correlation of the factors to each other and the release amount are quantitatively assessed.
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