title: AUC-guided dosing of tacrolimus prevents progressive systemic overexposure in renal transplant recipients.
abstract: BACKGROUND
  Tacrolimus has a narrow therapeutic window, and bioavailability is known to vary considerably between renal transplant recipients. Most centers still rely on measurement of trough levels, but there are conflicting reports on the correlation between tacrolimus trough levels and systemic exposure, as measured by the area-under-the-concentration-over-time curve (AUC((0-12h))).
  
  
  METHODS
  We developed and validated a two-compartmental population-based pharmacokinetic model with Bayesian estimation of tacrolimus systemic exposure. Subsequently, we used this model to apply prospectively AUC-guided dosing of tacrolimus in 15 consecutive renal transplant recipients. The main objective was to study intrapatient variability in the course of time.
  
  
  RESULTS
  Bayesian forecasting with a two-point sampling strategy, a trough level, and a second sample obtained between two and four hours post-dose significantly improved the squared correlation with the AUC((0-12h)) (r(2)= 0.94). Compared with trough level monitoring only, this approach reduced the 95%-prediction interval by 50%. The Bayesian approach proved to be feasible in clinical practice, and provided accurate information about systemic tacrolimus exposure in individual patients. In the AUC-guided dosing cohort the apparent clearance of tacrolimus decreased gradually over time, which was not reflected in corresponding trough levels.
  
  
  CONCLUSIONS
  This simple, flexible method provides the opportunity to tailor immunosuppression, and should help minimize tacrolimus-related toxicity, such as nephrotoxicity and post-transplant diabetes mellitus.
authors.affiliation: Department of Nephrology, Leiden University Medical Center, Leiden, The Netherlands. Emscholten@lumc.nl
authors.forename: Eduard M
authors.initials: EM
authors.lastname: Scholten
authors.forename: Serge C L M
authors.initials: SC
authors.lastname: Cremers
authors.forename: Rik C
authors.initials: RC
authors.lastname: Schoemaker
authors.forename: Ajda T
authors.initials: AT
authors.lastname: Rowshani
authors.forename: Erik J
authors.initials: EJ
authors.lastname: van Kan
authors.forename: Jan
authors.initials: J
authors.lastname: den Hartigh
authors.forename: Leendert C
authors.initials: LC
authors.lastname: Paul
authors.forename: Johan W
authors.initials: JW
authors.lastname: de Fijter
mesh_terms: D000328:Adult; D000368:Aged; D019540:Area Under Curve; D001499:Bayes Theorem; D051544:Cytochrome P-450 CYP3A; D003577:Cytochrome P-450 Enzyme System / Q000502:physiology; D005260:Female; D006801:Humans; D007166:Immunosuppressive Agents / Q000008:administration & dosage / Q000493:pharmacokinetics*; D016030:Kidney Transplantation; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D016559:Tacrolimus / Q000008:administration & dosage / Q000493:pharmacokinetics*
chemical_list: D007166:Immunosuppressive Agents; D003577:Cytochrome P-450 Enzyme System; C104464:CYP3A protein, human; D051544:Cytochrome P-450 CYP3A; D016559:Tacrolimus