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External Assessment and Refinement of a Population Pharmacokinetic Model to Guide Tacrolimus Dosing in Pediatric Heart Transplant.

Joseph E RowerAutumn M McKniteBorah HongKevin P DalyKyle D HopeAntonio G CabreraKimberly M Molina
Published in: Pharmacotherapy (2023)
The immunosuppressant tacrolimus is a first-line agent to prevent graft rejection following pediatric heart transplant; however, it suffers from extensive inter-patient variability and a narrow therapeutic window. Personalized tacrolimus dosing may improve transplant outcomes by more efficiently achieving and maintaining therapeutic tacrolimus concentrations. We sought to externally validate a previously published population pharmacokinetic (PK) model that was constructed with data from a single site. Data were collected from Seattle, Texas, and Boston Children's Hospitals, and assessed using standard population PK modeling techniques in NONMEMv7.2. While the model was not successfully validated for use with external data, further covariate searching identified weight (p<0.0001 on both volume and elimination rate) as a model-significant covariate. This refined model acceptably predicted future tacrolimus concentrations when guided by as few as three concentrations (median prediction error = 7%; median absolute prediction error = 27%), supporting the potential clinical utility of the model to provide personalized tacrolimus dosing guidance.
Keyphrases
  • heart failure
  • healthcare
  • randomized controlled trial
  • big data
  • young adults
  • machine learning
  • type diabetes
  • adipose tissue
  • human health
  • risk assessment
  • insulin resistance
  • weight loss
  • data analysis
  • climate change