Amikacin initial dose in critically ill patients: a nonparametric approach to optimize a priori PK/PD target attainments in individual patients

Amikacin is commonly used for probabilistic antimicrobial therapy in critically ill patients with sepsis. Its narrow therapeutic margin makes it challenging to determine the right individual dose that ensures the highest efficacy target attainment rate (TAR) in this setting. This study aims to develop a new initial dosing approach for amikacin, by optimizing the TAR in this population. A population pharmacokinetic model was built with a learning dataset from critically ill patients who received amikacin. It was then used to design an initial dosing approach maximizing TAR for a target peak concentration over the MIC ratio (Cmax/MIC) ≥ 8 or daily area under the curve over the MIC ratio (AUC/MIC) ≥ 75.In the included 166 patients, 53% had Cmax ≥ 64 mg/L with a median dose of 23.4 mg/kg. A two-compartment model with creatinine clearance and body surface area as covariates best described the data and showed good predictive performance. Our dosing approach was successful in optimizing TAR for Cmax/MIC, with a rate of 92.9% versus 67.9% using a 30 mg/kg regimen, based on an external subset of data and assuming a MIC = 8 mg/L. Mean optimal doses were higher (3.5± 0.5 g) than with 30 mg/kg regimen (2.1± 0.3 g). Suggested doses varied with the MIC, the target index and desired TAR threshold. A dosing algorithm based on the method is proposed for large range of patient covariates. Clinical studies are necessary to confirm efficacy and safety of this optimized dosing approach.