Population Pharmacokinetics of Meropenem and Vaborbactam Based on Data from Noninfected Subjects and Infected Patients

• Published in: Antimicrobial agents and chemotherapy Vol. 65; no. 9; p. e0260620
• Main Authors: Trang, M., Griffith, D. C., Bhavnani, S. M., Loutit, J. S., Dudley, M. N., Ambrose, P. G., Rubino, C. M.
• Format: Journal Article
• Language: English
• Published: United States American Society for Microbiology 17.08.2021
• Subjects: Anti-Bacterial Agents - therapeutic use; Boronic Acids; Drug Combinations; Heterocyclic Compounds, 1-Ring; Humans; Meropenem; Pharmacology; meropenem; vaborbactam; population pharmacokinetics
• ISSN: 0066-4804; 1098-6596; 1098-6596
• DOI: 10.1128/AAC.02606-20

Meropenem-vaborbactam is a broad-spectrum carbapenem–beta-lactamase inhibitor combination approved in the United States and Europe to treat patients with complicated urinary tract infections and in Europe for other serious bacterial infections, including hospital-acquired and ventilator-associated pneumonia. Population pharmacokinetic (PK) models were developed to characterize the time course of meropenem and vaborbactam using pooled data from two phase 1 and two phase 3 studies. Meropenem-vaborbactam is a broad-spectrum carbapenem–beta-lactamase inhibitor combination approved in the United States and Europe to treat patients with complicated urinary tract infections and in Europe for other serious bacterial infections, including hospital-acquired and ventilator-associated pneumonia. Population pharmacokinetic (PK) models were developed to characterize the time course of meropenem and vaborbactam using pooled data from two phase 1 and two phase 3 studies. Multicompartment disposition model structures with linear elimination processes were fit to the data using NONMEM 7.2. Since both drugs are cleared primarily by the kidneys, estimated glomerular filtration rate (eGFR) was evaluated as part of the base structural models. For both agents, a two-compartment model with zero-order input and first-order elimination best described the pharmacokinetic PK data, and a sigmoidal Hill-type equation best described the relationship between renal clearance and eGFR. For meropenem, the following significant covariate relationships were identified: clearance (CL) decreased with increasing age, CL was systematically different in subjects with end-stage renal disease, and all PK parameters increased with increasing weight. For vaborbactam, the following significant covariate relationships were identified: CL increased with increasing height, volume of the central compartment ( V c ) increased with increasing body surface area, and CL, V c , and volume of the peripheral compartment were systematically different between phase 1 noninfected subjects and phase 3 infected patients. Visual predictive checks demonstrated minimal bias, supporting the robustness of the final models. These models were useful for generating individual PK exposures for pharmacokinetic-pharmacodynamic (PK-PD) analyses for efficacy and Monte Carlo simulations to evaluate PK-PD target attainment.