Optimization of Ganciclovir and Valganciclovir Starting Dose in Children by Machine Learning.

Journal: Clinical pharmacokinetics
PMID: 38492206

Abstract

BACKGROUND AND OBJECTIVES: Ganciclovir (GCV) and valganciclovir (VGCV) show large interindividual pharmacokinetic variability, particularly in children. The objectives of this study were (1) to develop machine learning (ML) algorithms trained on simulated pharmacokinetics profiles obtained by Monte Carlo simulations to estimate the best ganciclovir or valganciclovir starting dose in children and (2) to compare its performances on real-world profiles to previously published equation derived from literature population pharmacokinetic (POPPK) models achieving about 20% of profiles within the target.

Authors

  • Laure Ponthier
    Inserm, Univ. Limoges, CHU Limoges, Pharmacology & Toxicology, Limoges, France.
  • Julie Autmizguine
    Research Center, Centre Hospitalier Universitaire Sainte-Justine, Montreal, QC, Canada.
  • Benedicte Franck
    Department of Clinical and Biological Pharmacology and Pharmacovigilance, Clinical Investigation Center, CIC-P 1414, Rennes, France.
  • Anders Åsberg
    Department of Transplantation Medicine, Oslo University Hospital, Rikshospitalet, Oslo, Norway.
  • Philippe Ovetchkine
    Department of Pediatrics, Centre Hospitalier Universitaire Sainte-Justine, Montreal, QC, Canada.
  • Alexandre Destere
    Département de Pharmacologie et de Pharmacovigilance, CHU de Nice, Université Côte d'Azur, France.
  • Pierre Marquet
    University of Limoges, UMR 1248.
  • Marc Labriffe
    University of Limoges, IPPRITT, Limoges, France.
  • Jean-Baptiste Woillard
    P&T, Unité Mixte de Recherche 1248 Université de Limoges, Institut National de la Santé et de la Recherche Médicale, Limoges, France.

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