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Population Pharmacokinetics of Polymyxin B and Dosage Optimization in Renal Transplant Patients

Authors
  • Li, Ying
  • Deng, Yang
  • Zhu, Zhen-Yu
  • Liu, Yi-Ping
  • Xu, Ping
  • Li, Xin
  • Xie, Yue-Liang
  • Yao, Heng-Chang
  • Yang, Liu
  • Zhang, Bi-Kui
  • Zhou, Yan-Gang
Type
Published Article
Journal
Frontiers in Pharmacology
Publisher
Frontiers Media SA
Publication Date
Aug 25, 2021
Volume
12
Identifiers
DOI: 10.3389/fphar.2021.727170
PMID: 34512352
PMCID: PMC8424097
Source
PubMed Central
Keywords
Disciplines
  • Pharmacology
  • Original Research
License
Unknown

Abstract

Currently, polymyxin B has been widely used in the treatment of multidrug-resistant Gram-negative pathogen infections. Due to the limited pharmacokinetic/pharmacodynamic data, the optimal dosage regimen for the recently proposed therapeutic target of the area under the concentration-time curve over 24 h in steady state divided by the minimum inhibitory concentration 50–100 mg⋅h/L has not yet been established. Moreover, most studies have focused on critically ill patients, yet there have been no studies in the field of renal transplantation. To optimize the dosage strategy and reduce the risk of toxicity, a population pharmacokinetics model of polymyxin B with the Phoenix NLME program was developed in our study. A total of 151 plasma samples from 50 patients were collected in the present study. Polymyxin B plasma concentrations were measured by high-performance liquid chromatography-tandem mass spectrometry. A one-compartment model adequately described the data, and the clearance and volume of distribution were 1.18 L/h and 12.09 L, respectively. A larger creatinine clearance was associated with increased clearance of polymyxin B ( p < 0.01). Monte Carlo simulation showed that a regimen of a 75 mg loading dose with a 50 mg maintenance dose was a better option to achieve an optimal therapeutic effect (minimum inhibitory concentration ≤1 mg/L) and to reduce the incidence of side effects for patients with renal impairments. The developed model suggested that dosing adjustment should be based on renal function in renal transplant patients.

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