title: Improved prediction of   tacrolimus concentrations   early after kidney   transplantation using   theory-based   pharmacokinetic modelling.
abstract: OBJECTIVE
  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.
  
  
  CONCLUSIONS
  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.
authors.forename: Elisabet
authors.initials: E
authors.lastname: Størset
authors.forename: Nick
authors.initials: N
authors.lastname: Holford
authors.forename: Stefanie
authors.initials: S
authors.lastname: Hennig
authors.forename: Troels K
authors.initials: TK
authors.lastname: Bergmann
authors.forename: Stein
authors.initials: S
authors.lastname: Bergan
authors.forename: Sara
authors.initials: S
authors.lastname: Bremer
authors.forename: Anders
authors.initials: A
authors.lastname: Åsberg
authors.forename: Karsten
authors.initials: K
authors.lastname: Midtvedt
authors.forename: Christine E
authors.initials: CE
authors.lastname: Staatz
mesh_terms: D000328:Adult; D001499:Bayes Theorem; D001682:Biological Availability; D051544:Cytochrome P-450 CYP3A / Q000235:genetics; D005260:Female; D005838:Genotype; D006801:Humans; D007166:Immunosuppressive Agents / Q000493:pharmacokinetics*; D016030:Kidney Transplantation; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D011239:Prednisolone / Q000008:administration & dosage; D016559:Tacrolimus / Q000493:pharmacokinetics*
chemical_list: D007166:Immunosuppressive Agents; D011239:Prednisolone; C510164:CYP3A5 protein, human; D051544:Cytochrome P-450 CYP3A; D016559:Tacrolimus