1. © 2010 Universitair Ziekenhuis Gent 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 (2), Ron Mathot (3) (1) Ghent University Hospital, Belgium (2) Erasmus MC, Rotterdam, the Netherlands (3) AMC, Amsterdam, the Netherlands

2. © 2010 Universitair Ziekenhuis Gent underexposureoverexposure nephrotoxicity malignancy infections graft rejection Tacrolimus: therapeutic drug monitoring Pre- dose concentrations (C 0 ) Area under the concentration time curve (12- hour-AUC) Abbreviated AUC C 0, C 60, C 180 concentrations W Zhao et al. Ther drug monit, 2011 Abbreviated AUC C 0, C 60, C 180 concentrations W Zhao et al. Ther drug monit, 2011

3. © 2010 Universitair Ziekenhuis Gent Tacrolimus clearance in de novo pediatric kidney recipients related to: - body weight - hematocrit - CYP3A5 polymorphism Zhao et al. Clinical Pharmacology & Therapeutics 2009 > 1 year - cortocosteroids - antiviral prophylaxis + antihypertensives

4. © 2010 Universitair Ziekenhuis Gent Objectives  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

5. © 2010 Universitair Ziekenhuis Gent Patients and methods  Retrospective cohort study  anthropometric measurements  laboratory parameters  concomitant medications  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®

6. © 2010 Universitair Ziekenhuis Gent Patients and methods  Calculation of 12-hour AUC using Bayesian analysis Pharmacokinetic analysis  non-linear mixed-effects modelling (NONMEM)  structural model o ral clearance, inter-compartment clearance, volume of distribution, the delay between ingestion and start of absorption, absorption rate constant  co-variate analysis 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 Rotterdam: 4 hour AUC 104 profiles in 54 children C 0 C 10 C 30 C 80 C 120 C 240 Rotterdam: 4 hour AUC 104 profiles in 54 children C 0 C 10 C 30 C 80 C 120 C 240 1- 5 profiles per child

7. © 2010 Universitair Ziekenhuis Gent Baseline characteristic number (total n= 54) median (IQR) range% of total Gender (boys)28 52 Age (years) 11.1 (6.2)3.8 - 18.4 Time since commencement TAC (months) 8.1 (7.2)1.6 - 61.3 Time since transplantation (months) 16.2 (24.9)11.4 – 124 Donor (deceased)26 48 Pre-emptive transplantation (yes)13 24 Weight (kg) 38.6 (26)15 - 86 Height (cm) 139 (31)100 - 176 Body surface area (m²) 1.22 (0.6)0.7 – 2.1 7 children weight <20kg

8. © 2010 Universitair Ziekenhuis Gent Results Laboratory measurements number (total n= 54) median (IQR) range% of total CYP3A5 genotype (n=49)  *1/*1  *1/*3  *3/*3 1 12 36 2 25 73 ABCB1 C->T genotype (n=49)  T/C  C/C  T/T 32 9 8 65 19 16 Creatinine (µmol/l) 87 (61)24 - 191 Albumine (g/l) 43 (5)30 - 49 γGT (U/l) 13 (9)4 - 118 Hematocrit 0.34 (0.05)0.21 -0. 44 eGFR Schwartz (ml/min/1.73m²) 62 (30)31 - 194

9. © 2010 Universitair Ziekenhuis Gent Concomitant medications (n= 51) immunosuppression mycophenolate mofetiln= 30 (80%) prednisolone n= 41 (59%) azathioprinen= 3 (6%)antihypertensives Ca-channel blockersn= 16 (31%) beta- blockersn= 7 (14%) Ace-i/ ARBn= 25 (48%) thiazide diureticsn= 8 (16%) loop diureticsn= 1 (2%) antibiotics trimethoprim/co-trimoxazolen= 4 (8%) nitrofurantoinen= 4 (8%) growth hormone growth hormone n= 6 (12%)anaemia erythropoietinn= 3 (6%) ferrous fumaraten= 12 (24%) vitamin D analogues cholecalciferoln= 3 (6%) 1-alfacalcidoln= 8 (16%)

10. © 2010 Universitair Ziekenhuis Gent CYP3A5 and daily tacrolimus dose baseline 0.16 mg/kg/day 0.12 mg/kg/day all profiles P = 0.02 P = 0.004 0.16 mg/kg/day 0.11 mg/kg/day

11. © 2010 Universitair Ziekenhuis Gent Tacrolimus oral 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 Final model Structural model weight (not age) Co-variate analysis CYP3A5*1 allele gamma glutamyl transpeptidase Hematocrit internal validation

12. © 2010 Universitair Ziekenhuis Gent Dose simulations 0.025 mg/kg 0.05 mg/kg 0.1 mg/kg 0.2 mg/kg CYP3A5 *3/*3CYP3A5 *1/*3

13. © 2010 Universitair Ziekenhuis Gent Limitations  No data set for external validation  Pharmacokinetic profiles generated over 10 years  No uniformity in pharmacokinetic profiles between 2 centers

14. © 2010 Universitair Ziekenhuis Gent Conclusions  low weight, CYP3A5*1 allele, low gamma glutamyl transpeptidase and low hematocrit are associated with a higher tacrolimus clearance in children > 1 years following kidney transplantation  no association between tacrolimus clearance and age  no association between tacrolimus clearance and concomitant medications

15. © 2010 Universitair Ziekenhuis Gent IPTA, San Francisco, California 2015

16. © 2010 Universitair Ziekenhuis Gent Model validation observed median predicted median

17. © 2010 Universitair Ziekenhuis Gent Pharmacokinetic profiles (AUC) distribution N= 120 39 - 209 h x ng/ml 25 th percentile80 75 th percentile120 h x ng/ml