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© 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
© 2010 Universitair Ziekenhuis Gent
Tacrolimus: therapeutic drug monitoring
Pre- dose concentrations (C0)
Pre- dose concentrations (C0)
Area under the concentration time curve (12- hour-AUC)
Area under the concentration time curve (12- hour-AUC)
Abbreviated AUC
C0, C60, C180
concentrations
W Zhao et al. Ther drug monit, 2011
Abbreviated AUC
C0, C60, C180
concentrations
W Zhao et al. Ther drug monit, 2011
© 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
© 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
© 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 criteriaInclusion 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®
© 2010 Universitair Ziekenhuis Gent
Patients and methods
Calculation of 12-hour AUC using Bayesian analysis
Pharmacokinetic analysisPharmacokinetic 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
Amsterdam: 2 hour AUC
16 profiles in 9 children
C0 C120
Amsterdam: 2 hour AUC
16 profiles in 9 children
C0 C120
Rotterdam: 4 hour AUC
104 profiles in 54 children
C0 C10 C30 C80 C120 C240
Rotterdam: 4 hour AUC
104 profiles in 54 children
C0 C10 C30 C80 C120 C2401- 5 profiles
per child
© 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
© 2010 Universitair Ziekenhuis Gent
ResultsLaboratory measurements number
(total n= 54)median(IQR)
range % of total
CYP3A5 genotype (n=49)*1/*1*1/*3 *3/*3
1
1236
2
2573
ABCB1 C->T genotype (n=49)T/CC/CT/T
3298
651916
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
© 2010 Universitair Ziekenhuis Gent
Concomitant medications (n= 51)
immunosuppressionimmunosuppression• mycophenolate mofetil n= 30 (80%)
• prednisolone n= 41 (59%)
• azathioprine n= 3 (6%)
antihypertensivesantihypertensives• Ca-channel blockers n= 16 (31%)
• beta- blockers n= 7 (14%)
• Ace-i/ ARB n= 25 (48%)
• thiazide diuretics n= 8 (16%)
• loop diuretics n= 1 (2%)
antibioticsantibiotics• trimethoprim/co-trimoxazole n= 4 (8%)
• nitrofurantoine n= 4 (8%)
growth hormonegrowth hormone n= 6 (12%)
anaemia anaemia • erythropoietin n= 3 (6%)
• ferrous fumarate n= 12 (24%)
vitamin D analoguesvitamin D analogues• cholecalciferol n= 3 (6%)
• 1-alfacalcidol n= 8 (16%)
© 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
© 2010 Universitair Ziekenhuis Gent
Tacrolimus oral clearance
Univariate analysisUnivariate 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 modelFinal model
Structural modelStructural model
• weight (not age)
Co-variate analysisCo-variate analysis
• CYP3A5*1 allele • gamma glutamyl
transpeptidase• Hematocrit
internal validation
© 2010 Universitair Ziekenhuis Gent
Dose simulations
0.025 mg/kg
0.05 mg/kg
0.1 mg/kg
0.2 mg/kg
CYP3A5 *3/*3 CYP3A5 *1/*3
© 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
© 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
© 2010 Universitair Ziekenhuis Gent
IPTA, San Francisco, California 2015
© 2010 Universitair Ziekenhuis Gent
Model validation
0 1 2 3 4
0
10
20
30
time (h)
tacr
olim
us
con
c (
g/L
)
observed median
predicted median
© 2010 Universitair Ziekenhuis Gent
Pharmacokinetic profiles (AUC) distribution
N= 120
39 - 209 h x ng/ml
25th percentile 80
75th percentile 120
h x ng/ml
h x ng/ml