4.5 Article

Improved prediction of tacrolimus concentrations early after kidney transplantation using theory-based pharmacokinetic modelling

Journal

BRITISH JOURNAL OF CLINICAL PHARMACOLOGY
Volume 78, Issue 3, Pages 509-523

Publisher

WILEY
DOI: 10.1111/bcp.12361

Keywords

Bayesian forecasting; kidney transplantation; population pharmacokinetics; tacrolimus; theory-based models

Funding

  1. University of Auckland
  2. South-Eastern Norway Regional Health Authority
  3. Norwegian Pharmaceutical Society
  4. Shipowner Tom Wilhelmsens Foundation
  5. University of Queensland

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AIMS The aim was to develop a theory-based population pharmacokinetic model of tacrolimus in adult kidney transplant recipients and to externally evaluate this model and two previous empirical models. METHODS Data were obtained from 242 patients with 3100 tacrolimus whole blood concentrations. External evaluation was performed by examining model predictive performance using Bayesian forecasting. RESULTS Pharmacokinetic disposition parameters were estimated based on tacrolimus plasma concentrations, predicted from whole blood concentrations, haematocrit and literature values for tacrolimus binding to red blood cells. Disposition parameters were allometrically scaled to fat free mass. Tacrolimus whole blood clearance/bioavailability standardized to haematocrit of 45% and fat free mass of 60 kg was estimated to be 16.1 l h(-1) [95% CI 12.6, 18.0 l h(-1)]. Tacrolimus clearance was 30% higher (95% CI 13, 46%) and bioavailability 18% lower (95% CI 2, 29%) in CYP3A5 expressers compared with non-expressers. An Emax model described decreasing tacrolimus bioavailability with increasing prednisolone dose. The theory-based model was superior to the empirical models during external evaluation displaying a median prediction error of -1.2% (95% CI -3.0, 0.1%). Based on simulation, Bayesian forecasting led to 65% (95% CI 62, 68%) of patients achieving a tacrolimus average steady-state concentration within a suggested acceptable range. CONCLUSION A theory-based population pharmacokinetic model was superior to two empirical models for prediction of tacrolimus concentrations and seemed suitable for Bayesian prediction of tacrolimus doses early after kidney transplantation.

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