Therapeutic Drug Monitoring-Based Population Pharmacokinetics of Amikacin in Patients at a Teaching Hospital

TL;DR

This study uses drug monitoring and population modeling to optimize amikacin dosing for better treatment outcomes in patients.

Contribution

The study integrates therapeutic drug monitoring with population pharmacokinetics to optimize amikacin dosing in Brazilian patients.

Findings

A one-compartment model best described amikacin pharmacokinetics with Cl of 1.49 L/h and Vc of 23.18 L.

The model can characterize amikacin profiles in Brazilian patients undergoing drug monitoring.

Combining drug monitoring with population analysis helps optimize dosing in special populations.

Abstract

Background: Amikacin is still an essential antimicrobial to treat life-threatening infections, including multidrug-resistant microorganisms. The effectiveness of treatment has been correlated with the Cmax/MIC ratio, with a ratio of 8 being recommended, which is difficult to reach in some patients. Appropriate antibiotic exposure is important for knowing the disposition of the drug in the population. Objectives: We aimed to integrate therapeutic drug monitoring and a populational pharmacokinetic model to assess an optimal dose regimen and respective plasma exposure. Methods: Plasma levels of amikacin in peaks and troughs were determined by LC-MS/MS. The pharmacokinetic parameter was estimated to use nonlinear mixed effect modeling in Monolix® software. The probability of target attainment was also determined using the Simulx™ software. Results: A total of 39 patients were enrolled. A one-compartment model with proportional error model best described amikacin pharmacokinetic parameters, providing a Cl of 1.49 L/h and Vc of 23.18 L. The model developed could characterize the pharmacokinetic profile in Brazilian patients who underwent therapeutic drug monitoring. Conclusions: Amikacin therapeutic drug monitoring should be associated with population pharmacokinetic analysis in dose optimization and individualization, helping maintain appropriate drug exposure in special populations such as critically ill patients. This strategy may contribute to enhancing clinical outcomes.

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