External assessment and refinement of a population pharmacokinetic model to guide tacrolimus dosing in pediatric heart transplant

Author:

Rower Joseph E.12ORCID,McKnite Autumn1ORCID,Hong Borah3ORCID,Daly Kevin P.4ORCID,Hope Kyle D.5ORCID,Cabrera Antonio G.56ORCID,Molina Kimberly M.6ORCID

Affiliation:

1. Department of Pharmacology and Toxicology University of Utah College of Pharmacy Salt Lake City Utah USA

2. Center for Human Toxicology University of Utah College of Pharmacy Salt Lake City Utah USA

3. Division of Pediatric Cardiology University of Washington and Seattle Children's Hospital Seattle Washington USA

4. Department of Pediatric Cardiology Harvard Medical School/Boston Children's Hospital Boston Massachusetts USA

5. Department of Pediatrics, Lillie Frank Abercrombie Division of Pediatric Cardiology, Texas Children's Hospital Baylor College of Medicine Houston Texas USA

6. Division of Pediatric Cardiology University of Utah/Intermountain Primary Children's Hospital Salt Lake City Utah USA

Abstract

AbstractStudy ObjectiveThe 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 SourceData were collected from Seattle, Texas, and Boston Children's Hospitals, and assessed using standard population PK modeling techniques in NONMEMv7.2.Main ResultsWhile 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%).ConclusionThese findings support the potential clinical utility of a population PK model to provide personalized tacrolimus dosing guidance.

Funder

National Heart, Lung, and Blood Institute

Publisher

Wiley

Subject

Pharmacology (medical)

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