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Predicting Paediatric Tobramycin Pharmacokinetics with Five Different Methods
Joseph Standing, Elizabeth Greening, Victoria Holden, Susan Picton, Nicola Young, Henry Chrystyn,
Mats Karlsson
Uppsala Universitet, SwedenSt James’s University Hospital, Leeds, UK
University of Huddersfield, UK
Predicting Paediatric Tobramycin Pharmacokinetics with Five Different
Methods
“Children are not small adults”– Differences (Kearns 2003 NEJM)
“Children are just small adults”– Similarities (Anderson 2008 Ann Rev PT)
• When and how can adult PK data help with paediatric analysis?
Predicting Paediatric Tobramycin Pharmacokinetics with Five Different
Methods
• Aminoglycoside
• Mainly Gm-ve activity• Blind therapy in feb. neutropaenia
(in Leeds)
• Once daily dosing (Maglio 2002)
Predicting Paediatric Tobramycin Pharmacokinetics with Five Different
Methods
• Log P = -7.3 (DiCicco 2002)
• Freely soluble in water
• Renal elimination
• Narrow therapeutic index– Peaks >10mg/L (efficacy)
– AUC <100mg.hr/L (toxicity)
Predicting Paediatric Tobramycin Pharmacokinetics with Five Different
Methods
• ADULT INDEX (Aarons 1989 BJCP):
– 97 adults
– 322 observations
– 16-85yrs, – CrCl 10-166mL/min (Cockroft Gault)
– Median 2 samples per dose
Predicting Paediatric Tobramycin Pharmacokinetics with Five Different
Methods
• PAEDIATRIC INDEX:
– 112 children,
– 650 observations
– 1-16yrs – CrCl 16-173mL/min (Anderson 2008)
– Median 2 samples per dose
Predicting Paediatric Tobramycin Pharmacokinetics with Five Different
Methods
• PAEDIATRIC TEST:
– 54 children
– 110 observations
– 1-12yrs– CrCl 29-101mL/min (Anderson 2008)
– 2 samples per dose
Predicting Paediatric Tobramycin Pharmacokinetics with Five Different
Methods
Predict PAEDIATRIC TEST with:
1. ADULT INDEX
2. PAEDIATRIC INDEX
3. Pooled ADULT/PAEDS INDEX
4. PAEDIATRIC INDEX with NWPRIOR
5. PAEDIATRIC INDEX with TNPRIOR
Priors in NONMEM
• Use of prior knowledge (Gisleskog 2002)
• NWPRIOR = Normal / Wishart-1
– Fixed and random effects– No prior on residual variability
• TNPRIOR = Normal / Normal– Priors on all parameters
Aims
• Evaluate adult data to predict paediatric PK
• Choose model to recommend dosing in children
Overview
• Introduction
• Aims
• Method
• Results
• Conclusions
Method
• PK Model (NONMEMVI FOCEI)
–2 compartment
–CL scaled to CrCl
–VD and VP scaled to wt
–Q scaled to wt0.75
–BOV on F for each dose
–Proportional residual error(Aarons 2005 BJCP Editorial)
Method
1. Analyse each index dataset2. Take final parameter estimates,
run PAEDIATRIC TEST MAXEVAL = 0
OFVMeasures overall fit
Method
3. Calculate patient averaged % prediction errors
(PRED-OBS) x 100
PRED
(IPRED-OBS) x 100
IPRED
4. Reduce paediatric index to half, quarter, eighth original size
Overview
• Introduction
• Aims
• Method
• Results
• Conclusions
Results
• PAEDIATRIC TEST OFV with params from each method (MAXEVALS=0)
– Adults: 316.5
– Paeds: 295.6
– Pooled: 304.1
– NWPRIOR: 312.8
– TNPRIOR: 297.5
Results
Test Data Versus Paediatric Index Population Prediction (log scale as proportional residual error)
1
10
100
1 10 100
Population predicted conc (mg/L)
Ob
serv
ed t
ob
ram
ycin
co
nc
(mg
/L)
Patient averaged prediction error:
9.2%(-5.2,23.6)
Patient averaged individual prediction error:
3.9%(1.7,6.2)
Test Data Versus Paediatric Index Individual Prediction(log scale as proportional residual error)
1
10
100
1 10 100
Individual predicted conc (mg/L)
Ob
serv
ed t
ob
ram
ycin
co
nc
(mg
/L)
PAEDIATRIC TEST predicted with PAEDATRIC INDEX
Results – Interim Summary
• PAEDIATRIC INDEX best at predicting PAEDIATRIC TEST
• What happens when paediatric data are less informative?– 56, 28 or 14 children in INDEX
Results• Reduced no. children in index (56, 28, 14)• Mean OFV from 5 random samples
Adult only TEST OFV: 316.5
OFV of Paediatric Test Data versus Number of Children in Index Data
290
295
300
305
310
315
320
325
330
335
0 20 40 60 80 100 120
Number of children in index dataset
Tes
t O
FV Paediatric Index
Pooled Index
NWPRIOR Index
TNPRIOR Index
Results - Summary
• Bias in adult predictions
• As imprecision rises (with fewer children), adult bias becomes less important
How to predict whether it is worth including adult data?
Results
• For each INDEX dataset:
• Case deletion diagnostic (CDD)
– 14 children, remove 1
– Estimate remaining 13
– Evaluate OFV for removed child
– Repeat for all, sum OFVs
Results
• CDD result:
1. TNPRIOR: 227.0
2. Paeds: 254.5
3. NWPRIOR: 332.8
4. Pooled: 368.1OFV of Paediatric Test Data versus Number of Children in Index Data
290
295
300
305
310
315
320
325
330
335
0 20 40 60 80 100 120
Number of children in index dataset
Tes
t O
FV Paediatric Index
Pooled Index
NWPRIOR Index
TNPRIOR Index
ResultsFinal Model
• Pooled paediatric INDEX and TEST:
All Paediatric Data Population Predictions versus Observations (log scale)
0
1
10
100
0 1 10 100
Population predicted tobramycin conc (mg/L)
Ob
serv
ed t
ob
ram
ycin
co
nc
(mg
/L)
All Paediatric Data Individual Predictions versus Observations (log scale)
0
1
10
100
0 1 10 100
Individual predicted tobramycin conc (mg/L)O
bse
rved
to
bra
myc
in c
on
c (m
g/L
)
ResultsAll Paediatric Data Conditional Weighted Residual
Error versus Time After Dose
-5
-4
-3
-2
-1
0
1
2
3
4
5
0 14
Time after dose (hr)
CW
RE
S
All Paediatric Data Conditional Weighted Residual Error versus Population Predictions
-5
-4
-3
-2
-1
0
1
2
3
4
5
0 60
Population predicted tobramycin conc (mg/L)
CW
RE
S
Overview
• Introduction
• Aims
• Method
• Results
• Conclusions
Conclusions
• Best prediction of paed PK was with paed PK!
• Whether to add adult data depends on relative informativeness
(CDD could help with this)
• Model for dose recommendation (+ TDM) developed
Acknowledgements
Patients who took part
• Leon Aarons - adult data from:
http://www.rfpk.washington.edu/
• Uppsala colleagues
• Pfizer for postdoc funding (JS)
References• Aarons L, Vozeh S Wenk M, Weiss P, Follath F. British Journal of Clinical
Pharmacology, 1989;28:305-14. Raw data from: http://www.rfpk.washington.edu/
• Aarons L. 2005. Physiologically based pharmacokinetic modelling: a sound mechanistic basis is needed. British Journal of Clinical Pharmacology, 60:581-3. Anderson BJ & Holford NHG. Annual Review of Pharmacology & Toxicology, 2008;48:12.1-12.30.
• DiCicco M, Duong T, Chu A, Jansen SA. 2002. J Mat Res B Appl Biomater, 65:137-49.
• Gisleskog PO, Karlsson MO, Beal SL. 2002. Journal of Pharmacokinetics and Pharmacodynamics, 29:473-505.
• Kearns GL, Abdel-Rahman SM, Alander SW, Blowey DL, Leeder JS, Kauffman RE. 2003. New England Journal of Medicine, 349:1157-67.
• Maglio D, Nightingale CH, Nicolau DP. 2002. International Journal of Antimicrobial Agants, 19:341-8.
• Martindale. 2007. Martindale, the complete drug reference. 35th Edition, Pharmaceutical Press, London, UK.
Extra Slides
NWPRIOR Degrees of Freedom
Give DOF for each ETA prior
SE(2) = 2 (2/(N-1))½
2 = variance (ETA)
N = DOF
CrCl Estimation from SeCr
• Aarons used Cockroft Gault: = 150-age*wt (+/-10% m/f)
SeCr
• “Anderson Holford” in children= CPR
SeCr
Results