Despite being in clinical use for about 6 decades, vancomycin dosing remains perplexing and complex.Methods:
A population pharmacokinetic modeling and simulation approach was used to evaluate the efficiency of the current nomogram-based dosing of vancomycin. Serum vancomycin concentrations were obtained as a part of routine therapeutic drug monitoring from two 500-bed academic medical centers. A population pharmacokinetic model was first built using these therapeutic drug monitoring data. Population pharmacokinetic modeling was conducted using NONMEM (7.2 and 7.3). The forward addition–backward elimination approach was used to test the covariate effects. Appropriate numerical and visual criteria were used as model diagnostics for checking model appropriateness and model qualification. The current nomogram efficiency was evaluated by determining the percentage of subjects in the therapeutic range (10–20 mg/L).Results:
A 2-compartment model with between-subject variability on clearance (CL), central volume of distribution (Vc), and peripheral volume of distribution best fit the data. Blood urea nitrogen, age, creatinine clearance, and hemodialysis status were significant covariates on clearance. Hemodialysis status was a significant covariate on Vc and peripheral volume of distribution. In the final model, creatinine clearance was retained as a covariate on CL whereas hemodialysis status was retained as covariate on both CL and Vc. Using Monte Carlo simulations, the current nomogram was optimized by the addition of a loading dose and reducing the maintenance doses. The current nomogram is suboptimal. Optimization of the nomogram resulted in >40% subjects consistently being in the therapeutic range at troughs collected after the first 6 doses.Conclusions:
CL and Vc differ markedly between patients undergoing hemodialysis and those not undergoing hemodialysis. Dosing nomogram based on these covariate relationships may potentially help in accurate dosing of vancomycin.