Population pharmacokinetics of linezolid and its major metabolites <scp>PNU</scp>‐142300 and <scp>PNU</scp>‐142586 in adult patients
Norihiro Sakurai, Hiroshi Kawaguchi, Junko Abe, Gaku Kuwabara, Waki Imoto, Wataru Shibata, Koichi Yamada, Hiroyuki Yasui, Yasutaka Nakamura, Hiroshi Kakeya
Abstract
Abstract Introduction Only a few reports are available on the population pharmacokinetic (PK) analysis of linezolid and its main metabolites. Therefore, we investigated the population PK of linezolid and its metabolites in adult patients treated with intravenous linezolid to identify the causative factors affecting pharmacokinetics, and evaluated the relationship between the parent compound and major metabolites PNU‐142300 and PNU‐142586. Methods Population PK analysis was performed using medical data collected from patients who were treated with intravenous linezolid (600 mg twice daily). We examined the impact of covariate candidates such as demographic characteristics and laboratory parameters. Simulations using the final model were investigated and used to estimate the plasma concentrations, trough concentrations ( C min ), and area under the curve (AUC) of linezolid and its metabolites, and the metabolite‐to‐parent ratios for C min and AUC were used to assess the accumulation of metabolites over linezolid. Results A total of 82 plasma concentrations from 23 patients were analyzed. The volume of distribution was estimated to be 47.1 L, assuming that linezolid and its metabolites were the same. The total clearance (CL) of linezolid, and CLs of PNU‐142300 and PNU‐142586 were influenced by creatinine clearance (CLcr), with population mean CLs of 3.86, 7.27, and 13.54 L/h, respectively. The C min and AUCs of linezolid and its metabolites and the ratios of metabolites per linezolid were predicted to increase exponentially with decreasing renal function. Conclusion We developed the first population PK model in which CLcr was incorporated as a covariate in the CL of linezolid and its metabolites. Using the final model, it was possible to predict the plasma concentration, C min , and AUC appropriately. The model was found to be a potentially useful tool for future studies on optimal dosing and toxicity analysis.