Literature DB >> 31094317

Effect of pharmacokinetic model misspecification on antibiotic probability of target attainment predicted by Monte Carlo simulation
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So Won Kim, Dong Jin Kim, Dae Young Zang, Dong-Hwan Lee.   

Abstract

OBJECTIVE: The first aim of this study was to compare the predictability of efficacy by Monte Carlo simulation between a true one-compartment model and a true two-compartment model for doripenem. The second aim was to explore how we can identify the usefulness of a one-compartment model when the pharmacokinetic/pharmacodynamic (PK/PD) indices between three misspecified one-compartment models and a true two-compartment model are compared.
MATERIALS AND METHODS: The reported two-compartment model parameters of two doripenem studies and a vancomycin study were used to generate 200 virtual concentration-time profiles for each study. Sparse and dense sampling designs were selected to build the one- and two-compartment models, respectively. The probability of target attainment (PTA) for the PK/PD indices were compared between the one- and two-compartment models of the same drug, applying the clinical breakpoint distribution of minimum inhibitory concentrations (MICs).
RESULTS: The simulated concentration-time profiles reproduced the original data well. In addition, PTAs were similar between the one- and two-compartment models when infusion time and MIC were the same in the doripenem studies. For vancomycin simulations, the maximum difference was 65.9% between a misspecified one-compartment model and the true two-compartment model.
CONCLUSION: When a misspecified one-compartment model was established with sparse sampling data, the PTA was significantly different from that of the two-compartment model. Thus, a useful PK model must be verified through diagnostic plots and visual predictive checks and the range of sampling time should be sufficient to explain the PK of a drug.

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Year:  2019        PMID: 31094317     DOI: 10.5414/CP203446

Source DB:  PubMed          Journal:  Int J Clin Pharmacol Ther        ISSN: 0946-1965            Impact factor:   1.366


  3 in total

1.  Predicting Antibiotic Effect of Vancomycin Using Pharmacokinetic/Pharmacodynamic Modeling and Simulation: Dense Sampling versus Sparse Sampling.

Authors:  Yong Kyun Kim; Jae Ha Lee; Hang-Jea Jang; Dae Young Zang; Dong-Hwan Lee
Journal:  Antibiotics (Basel)       Date:  2022-05-31

2.  Two Innovative Approaches to Optimize Vancomycin Dosing Using Estimated AUC after First Dose: Validation Using Data Generated from Population PK Model Coupled with Monte-Carlo Simulation and Comparison with the First-Order PK Equation Approach.

Authors:  Qingxia Liu; Huiping Huang; Baohua Xu; Dandan Li; Maobai Liu; Imam H Shaik; Xuemei Wu
Journal:  Pharmaceutics       Date:  2022-05-07       Impact factor: 6.525

3.  Impact of Sampling Period on Population Pharmacokinetic Analysis of Antibiotics: Why do You Take Blood Samples Following the Fourth Dose?

Authors:  So Won Kim; Dong Jin Kim; Dae Young Zang; Dong-Hwan Lee
Journal:  Pharmaceuticals (Basel)       Date:  2020-09-16
  3 in total

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