Model‐informed precision dosing of vancomycin for rapid achievement of target area under the concentration‐time curve: A simulation study

In this study, we aimed to evaluate limited sampling strategies for achieving the therapeutic ranges of the area under the concentration‐time curve (AUC) of vancomycin on the first and second day (AUC(0–24), AUC(24–48), respectively) of therapy. A virtual population of 1000 individuals was created using a population pharmacokinetic (PopPK) model, which was validated and incorporated into our model‐informed precision dosing tool. The results were evaluated using six additional PopPK models selected based on a study design of prospective or retrospective data collection with sufficient concentrations. Bayesian forecasting was performed to evaluate the probability of achieving the therapeutic range of AUC, defined as a ratio of estimated/reference AUC within 0.8–1.2. The Bayesian posterior probability of achieving the AUC(24–48) range increased from 51.3% (a priori probability) to 77.5% after using two‐point sampling at the trough and peak on the first day. Sampling on the first day also yielded a higher Bayesian posterior probability (86.1%) of achieving the AUC(0–24) range compared to the a priori probability of 60.1%. The Bayesian posterior probability of achieving the AUC at steady‐state (AUC(SS)) range by sampling on the first or second day decreased with decreased kidney function. We demonstrated that second‐day trough and peak sampling provided accurate AUC(24–48), and first‐day sampling may assist in rapidly achieving therapeutic AUC(24–48), although the AUC(SS) should be re‐estimated in patients with reduced kidney function owing to its unreliable predictive performance.