Identifying the Optimal Sampling Strategy for the Bayesian Estimation of Vancomycin AUC0–24 in Adult Hematologic Cancer Patients: Bayesian Estimation of Vancomycin AUC0–24 in an Adult Population with Hematologic Cancer: A. Duong et al

Background and objective: The latest consensus recommends using the ratio between the area under the curve over 24 h (AUC0–24) and minimal inhibitory concentration (MIC) as the therapeutic target for vancomycin in clinical practice, with a Bayesian approach and population pharmacokinetic (popPK) model being particularly recommended. While using both post-dose peak concentration (Cpeak) and pre-dose concentration (Ctrough) is more accurate than Ctrough alone, the optimal sampling strategy for estimating AUC0–24 is still unclear. The objective of this study was to determine the best sampling time(s) to estimate AUC0–24 using the Bayesian approach in these specific adult hematologic cancer patients. Methods: A virtual population (n = 7000) was simulated based on the distribution of the significant covariates (ideal body weight and estimated glomerular filtration rate) from the population used to develop the previous pharmacokinetic model. The dosing regimens from the Le Blanc et al. nomogram were used to generate, with NONMEM® (v.7.5), simulated pharmacokinetic (PK) profiles of one loading dose followed by three maintenance doses (steady state). Strategies involving two samples taken during earlier maintenance doses and one sample taken at steady state were tested using the Bayesian approach to predict PK parameters. These strategies were then evaluated for their ability to predict AUC0–24 at steady state (AUC0–24,ss) Results: For single-sample strategies, a sample taken anytime from 4 h post-dose can estimate AUC0–24,ss with precision similar to Ctrough (R2 ≈ 0.75), regardless of renal function (R2 ≈ 0.73–0.77). For two-sample strategies, taking samples at least midway through the dosing interval provides the highest precision for estimating AUC0–24,ss during the first two maintenance doses (R2 ≈ 0.75–0.77). In both strategies, using Cpeak did not yield as precise results as sampling midway through the dosing interval or at Ctrough. Conclusion: This study is the first to test multiple limited sampling strategies using a dosing nomogram stratified by renal function. The results show that vancomycin sampling can extend beyond traditional Cpeak and Ctrough without compromising the accuracy of maximum a posteriori Bayesian estimation of AUC0–24,ss, thereby providing an opportunity to investigate these limited sampling strategies combined with model-informed precision dosing in a clinical setting. [ABSTRACT FROM AUTHOR]