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Physiologically-Based Pharmacokinetic Modeling of Fluconazole Using Plasma and Cerebrospinal Fluid Samples From

Jacqueline G Gerhart1, Kevin M Watt2, Andrea Edginton3

  • 1Division of Pharmacotherapy and Experimental Therapeutics, University of North Carolina Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.

CPT: Pharmacometrics & Systems Pharmacology
|May 16, 2019
PubMed

Insights

This study adapted an adult fluconazole model for infants, accurately predicting drug levels in plasma and cerebrospinal fluid (CSF). A loading dose improved target attainment for treating fungal infections in neonates.

Area of Science:

  • Pharmacokinetics and Drug Metabolism
  • Pediatric Pharmacology
  • Infectious Diseases

Background:

  • Hematogenous Candida meningoencephalitis is a serious infection in infants.
  • Optimizing fluconazole dosing is crucial for effective treatment and minimizing toxicity in neonates.

Purpose of the Study:

  • To characterize fluconazole exposure in infant plasma and central nervous system (CNS).
  • To evaluate the achievement of a surrogate efficacy target using existing dosing guidelines.
  • To adapt an adult physiologically-based pharmacokinetic (PBPK) model for pediatric use.

Main Methods:

  • Scaled an adult fluconazole PBPK model to infants, incorporating age-dependent physiological parameters.
  • Optimized the PBPK model using extensive plasma and cerebrospinal fluid (CSF) sample data from preterm and term infants.
  • Simulated fluconazole concentrations to assess the attainment of the unbound area under the concentration-time curve (AUC) target.

Main Results:

  • The PBPK model demonstrated good predictive accuracy for fluconazole plasma (average fold error 0.73) and CSF concentrations (average fold error 1.14).
  • Simulations indicated that incorporating a 25 mg/kg loading dose accelerated the achievement of target drug exposure in both plasma and CSF.
  • The model successfully predicted fluconazole kinetics across a range of postmenstrual ages.

Conclusions:

  • Physiologically-based pharmacokinetic (PBPK) modeling is a valuable tool for predicting CNS drug exposure in pediatric populations.
  • A loading dose of fluconazole can enhance therapeutic efficacy in infants with Candida meningoencephalitis.
  • This PBPK model provides a foundation for optimizing fluconazole dosing strategies in neonates.

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