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

Abstract

Study Objective: 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 Source: Data were collected from Seattle, Texas, and Boston Children's Hospitals, and assessed using standard population PK modeling techniques in NONMEMv7.2. Main Results: 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%). Conclusion: These findings support the potential clinical utility of a population PK model to provide personalized tacrolimus dosing guidance.