1. Background Conclusions low weight, CYP3A5*1 allele, low gamma glutamyl transpeptidase and low hematocrit are associated with a higher tacrolimus clearance in children > 1 year following kidney transplantation no association between tacrolimus pharmacokinetics and age no association between tacrolimus pharmacokinetics and concomitant medications in our model to develop a population model for tacrolimus exposure in pediatric renal transplant recipients at least 1 year after transplantation to identify co-variates contributing to the variability in tacrolimus pharmacokinetics to develop individualized dosage recommendations POPULATION PHARMACOKINETICS OF TACROLIMUS IN STABLE PAEDIATRIC RENAL TRANSPLANT RECIPIENTS TRANSLATED INTO CLINICAL PRACTICE Agnieszka Prytuła (1) Karlien Cransberg (2) Antonia Bouts (3) Saskia de Wildt (2) Ron van Schaik (4) Ron Mathôt (5) ( 1) Ghent University Hospital (2) Erasmus MC - Sophia Children’s Hospital, Rotterdam (3) Emma Children’s Hospital, Amsterdam (4) Erasmus MC, Rotterdam (5) Academic Medical Center, Amsterdam under exposure over exposure nephro toxicity malignancy infections graft rejection Tacrolimus clearance in de novo pediatric kidney recipients is related to: body weight hematocrit CYP3A5 polymorphism Zhao et al. Clinical Pharm & Ther 2009 What changes > 1 year after transplantation ? - corticosteroids - antiviral prophylaxis + antihypertensive medications Objectives Patients and Methods Results Study design: retrospective cohort study; 54 patients included renal transplantation April 1993- June 2011 genetic analysis: CYP3A5*3 and ABCB1 C3435T polymorphism Inclusion criteria AUC at least 1 year after renal transplantation functioning allograft with eGFR> 30 ml/min/1.73m² at baseline on twice-daily tacrolimus formulation Prograft® Pharmacokinetic analysis non-linear mixed-effects modelling (NONMEM) structural model (oral clearance, inter-compartment clearance, volume of distribution, the delay between ingestion and start of absorption, absorption rate constant) co-variate analysis Rotterdam: 4 hour AUC 104 profiles in 45 children C 0 C 10 C 30 C 80 C 120 C 240 Rotterdam: 4 hour AUC 104 profiles in 45 children C 0 C 10 C 30 C 80 C 120 C 240 Amsterdam: 2 hour AUC 16 profiles in 9 children C 0 C 120 Amsterdam: 2 hour AUC 16 profiles in 9 children C 0 C 120 NONMEM analysis- tacrolimus clearance Univariate analysis P < 0.001 recombinant growth hormone P < 0.005 CYP3A5*1 allele gamma glutamyl transpeptidase 1-alfacalcidol ferrous fumarate P < 0.05 male gender hematocrit serum creatinine Baseline characteristics Number (% of total) Median (IQR) gender (boys)28 (52) age (years) 11.1 (6.2) time since commencement TAC (months) 8.1 (7.2) time since transplantation (months) 16.2 (24.9) CYP3A5 genotype (n=49)  *1/*1  *1/*3  *3/*3 1 (2) 12 (25) 36 (73) ABCB1 C->T genotype (n=49)  T/C  C/C  T/T 32 (65) 9 (19) 8 (16) 0.15 mg/kg/day0.12 mg/kg/day P = 0.04 Final model Structural model weight (not age ) Co-variate analysis CYP3A5*1 allele Gamma glutamyl transpeptidase hematocrit