Electronic-Nomogram-Guided Micafungin Dosing Regimen in Critically Ill Patients: A Population Pharmacokinetic…

Abstract

Objectives To develop a population pharmacokinetic model for micafungin and an electronic nomogram to support the selection of the optimal initial dosing regimen. Methods A retrospective, monocentric pharmacokinetic study was conducted in a digestive intensive care unit. Population pharmacokinetic modelling and covariate analysis were performed using Monolix.2024R1. Monte Carlo simulations were subsequently used to build the e-nomogram. Results Overall, 404 micafungin plasma concentrations obtained from 100 patients were analysed, including 40% with cirrhosis and/or a history of liver transplantation. The concentration-time data were adequately described by a linear one-compartment model. The estimated PK parameters (between-subject variability) were 17.3 L (15%) for volume of distribution and 0.85 L/h (25%) for clearance (Cl). Total body weight and total bilirubin were identified to influence volume of distribution and/or Cl. External model evaluation showed acceptable predictive performance for both population and individual predictions. Monte Carlo simulations suggested that the currently recommended regimen of 100 mg/d may be insufficient to achieve the pharmacokinetic/pharmacodynamic target for all Candida species when clinical breakpoint MIC values are considered. Conclusion The resulting RShiny application provides clinicians with a practical decision support tool for selecting the best loading and maintenance doses according to total body weight, BILI and the target pathogen, thereby maximising the probability of pharmacokinetic/pharmacodynamic target attainment.

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BibTeX

@article{bendjilalisabiani2026electronicnomogramguided,
  title = {{Electronic-Nomogram-Guided Micafungin Dosing Regimen in Critically Ill Patients: A Population Pharmacokinetic Study}},
  author = {Jean-Joseph Bendjilali-Sabiani and Ahlem Gammoudi and Matthieu Conseil and Samir Jaber and Yoann Cazaubon},
  journal = {International Journal of Antimicrobial Agents},
  year = {2026},
  month = aug,
  doi = {10.1016/j.ijantimicag.2026.107970},
  url = {https://hal.science/hal-05719578v1},
  note = {CC BY-NC-ND 4.0},
}

RIS

TY  - JOUR
TI  - Electronic-Nomogram-Guided Micafungin Dosing Regimen in Critically Ill Patients: A Population Pharmacokinetic Study
AU  - Jean-Joseph Bendjilali-Sabiani
AU  - Ahlem Gammoudi
AU  - Matthieu Conseil
AU  - Samir Jaber
AU  - Yoann Cazaubon
PY  - 2026
DA  - 2026/08/17
JO  - International Journal of Antimicrobial Agents
DO  - 10.1016/j.ijantimicag.2026.107970
UR  - https://hal.science/hal-05719578v1
AB  - Objectives To develop a population pharmacokinetic model for micafungin and an electronic nomogram to support the selection of the optimal initial dosing regimen. Methods A retrospective, monocentric pharmacokinetic study was conducted in a digestive intensive care unit. Population pharmacokinetic modelling and covariate analysis were performed using Monolix.2024R1. Monte Carlo simulations were subsequently used to build the e-nomogram. Results Overall, 404 micafungin plasma concentrations obtained from 100 patients were analysed, including 40% with cirrhosis and/or a history of liver transplantation. The concentration-time data were adequately described by a linear one-compartment model. The estimated PK parameters (between-subject variability) were 17.3 L (15%) for volume of distribution and 0.85 L/h (25%) for clearance (Cl). Total body weight and total bilirubin were identified to influence volume of distribution and/or Cl. External model evaluation showed acceptable predictive performance for both population and individual predictions. Monte Carlo simulations suggested that the currently recommended regimen of 100 mg/d may be insufficient to achieve the pharmacokinetic/pharmacodynamic target for all Candida species when clinical breakpoint MIC values are considered. Conclusion The resulting RShiny application provides clinicians with a practical decision support tool for selecting the best loading and maintenance doses according to total body weight, BILI and the target pathogen, thereby maximising the probability of pharmacokinetic/pharmacodynamic target attainment.
SN  - 0924-8579
SN  - 1872-7913
ER  -

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