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Aims: This study aims to establish a population pharmacokinetic (PK) model of teicoplanin in Chinese adult patients to evaluate the dosing regimen in the label sheet and optimize it. Methods: Nonlinear mixed‐effects modelling was used to estimate PK parameters. Monte Carlo simulations were used to evaluate the attainment of various dosing regimens in achieving the target trough concentrations in patients with normal or decreased renal function. Results: A total of 115 patients were enrolled in this retrospective study. Creatinine clearance (CrCL) and albumin (ALB) were identified as covariates on the clearance of teicoplanin. For the treatment of non‐complicated methicillin‐resistant Staphylococcus aureus (MRSA) infections in patients with normal renal function and serum ALB concentration, the recommended dosing regimen was 600 mg q12h with five administrations as the loading dose followed by 600 mg qd as the maintenance dose; for the treatment of serious and/or complicated MRSA infections, the recommended dosing regimen was 800 mg q12h with five administrations as the loading dose followed by 800 mg qd as the maintenance dose. It is worth noting that both the loading and maintenance doses ought to be modified based on the patient's renal function and serum ALB concentration. In addition, trough concentrations of teicoplanin were significantly increased every other week. Conclusions: Both loading dosing and maintenance dosing regimens were recommended to be adjusted according to patient's renal function and serum ALB concentration. In addition, it is necessary to perform follow‐up therapeutic drug monitoring of teicoplanin at least once every week. [ABSTRACT FROM AUTHOR]

Background: Presently, colistin is commercially available in two different forms, namely, colistin sulfate and its sulphomethylated derivative, colistimethate sodium (CMS). However, in the currently reported studies, most of the clinical studies on colistin for parenteral use are referred to as CMS. Data on the pharmacokinetics (PK), clinical efficacy, and side effects of colistin sulfate in clinical use have not been reported. Methods: This retrospective study was performed on carbapenem-resistant organism (CRO)-infected patients treated with colistin sulfate for more than 72 h. The population pharmacokinetic model was developed using the NONMEM program. The clinical outcomes including clinical treatment efficacy, microbiological eradication, and nephrotoxicity were assessed. Monte Carlo simulation was utilized to calculate the probability of target attainment (PTA) in patients with normal or decreased renal function. Results: A total of 42 patients were enrolled, of which 25 (59.52%) patients were considered clinical treatment success and 29 (69.06%) patients had successful bacteria elimination at the end of treatment. Remarkably, no patient developed colistin sulfate-related nephrotoxicity. A total of 112 colistin concentrations with a range of 0.28–6.20 mg/L were included for PK modeling. The PK characteristic of colistin was well illustrated by a one-compartment model with linear elimination, and creatinine clearance (CrCL) was identified as a covariate on the clearance of colistin sulfate that significantly explained inter-individual variability. Monte Carlo simulations showed that the recommended dose regimen of colistin sulfate, according to the label sheet, of a daily dose of 1–1.5 million IU/day, given in 2–3 doses, could attain PTA > 90% for MICs ≤ 0.5 μg/mL, and that a daily dose of 1 million IU/day could pose a risk of subtherapeutic exposure for MIC ≥1 μg/ml in renal healthy patients. Conclusion: Renal function significantly affects the clearance of colistin sulfate. A dose of 750,000 U every 12 h was recommended for pathogens with MIC ≤1 μg/ml. The dosage recommended by the label inserts had a risk of subtherapeutic exposure for pathogens with MIC ≥2 μg/ml. Despite higher exposure to colistin in patients with acute renal insufficiency, dose reduction was not recommended. [ABSTRACT FROM AUTHOR]

Background: Linezolid is associated with myelosuppression, which may cause failure in optimally treating bacterial infections. The study aimed to define the pharmacokinetic/toxicodynamic (PK/TD) threshold for critically ill patients and to identify a dosing strategy for critically ill patients with renal insufficiency. Methods: The population pharmacokinetic (PK) model was developed using the NONMEM program. Logistic regression modeling was conducted to determine the toxicodynamic (TD) threshold of linezolid-induced myelosuppression. The dosing regimen was optimized based on the Monte Carlo simulation of the final model. Results: PK analysis included 127 linezolid concentrations from 83 critically ill patients at a range of 0.25–21.61 mg/L. Creatinine clearance (CrCL) was identified as the only covariate of linezolid clearance that significantly explained interindividual variability. Thirty-four (40.97%) of the 83 patients developed linezolid-associated myelosuppression. Logistic regression analysis showed that the trough concentration (Cmin) was a significant predictor of myelosuppression in critically patients, and the threshold for Cmin in predicting myelosuppression with 50% probability was 7.8 mg/L. The Kaplan–Meier plot revealed that the overall median time from the initiation of therapy to the development of myelosuppression was 12 days. Monte Carlo simulation indicated an empirical dose reduction to 600 mg every 24 h was optimal to balance the safety and efficacy in critically ill patients with CrCL of 30–60 ml/min, 450 mg every 24 h was the alternative for patients with CrCL <30 ml/min, and 600 mg every 12 h was recommended for patients with CrCL ≥60 ml/min. Conclusion: Renal function plays a significant role in linezolid PKs for critically ill patients. A dose of 600 mg every 24 h was recommended for patients with CrCL <60 ml/min to minimize linezolid-induced myelosuppression. [ABSTRACT FROM AUTHOR]

Aims: Current FDA‐approved label recommends that the dosage of polymyxin B should be adjusted according to renal function. However, the correlation between polymyxin B pharmacokinetics (PK) and creatinine clearance (CrCL) is poor. This study aimed to develop a population PK model of polymyxin B in adult patients with various renal functions and to identify a dosing strategy. Methods: A retrospective PK study was performed in 32 adult patients with various renal function. Nonlinear mixed effects modelling was applied to build a population PK model of polymyxin B followed by Monte Carlo simulations which designed polymyxin B dosing regimens across various renal function. Results: Polymyxin B PK analyses included 112 polymyxin B concentrations at steady state from 32 adult patients, in which 71.9% of them were critically ill. In the final PK model, CrCL was the significant covariate on CL (typical value 1.59 L/h; between‐subject variability 13%). The mean (SD) individual empirical Bayesian estimate of CL was 1.75 (0.43) L/h. In addition, a new dosing strategy combining the PK/pharmacodynamic (PD) targets and Monte Carlo simulation indicated that the reduction of polymyxin B dose in patients with renal insufficiency improved the probability of achieving optimal exposure. For severe infections caused by organisms with minimum inhibitory concentration (MIC) ≥ 2 mg/L, a high daily dose of polymyxin B might be possible for bacterial eradication, but the risk of nephrotoxicity is increased. Conclusions: Renal function plays a significant role in polymyxin B PK, and the dose of polymyxin B should be adjusted according to CrCL in patients with renal insufficiency. [ABSTRACT FROM AUTHOR]