Predicting Paediatric
Tobramycin Pharmacokinetics
with Five Different Methods
Joseph Standing, Elizabeth Greening, Victoria Holden,
Susan Picton, Nicola Young, Henry Chrystyn,
Mats Karlsson
Uppsala Universitet, Sweden
St 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.
2.
3.
4.
5.
ADULT INDEX
PAEDIATRIC INDEX
Pooled ADULT/PAEDS INDEX
PAEDIATRIC INDEX with NWPRIOR
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 dataset
2. Take final parameter estimates,
run PAEDIATRIC TEST
MAXEVAL = 0
OFV
Measures 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:
– Paeds:
– Pooled:
– NWPRIOR:
– TNPRIOR:
316.5
295.6
304.1
312.8
297.5
Results
Test Data Versus Paediatric Index Population Prediction
Test Data Versus Paediatric Index Individual Prediction
(log scale as proportional residual error)
(log scale as proportional residual error)
100
Observed tobramycin conc (mg/L)
Observed tobramycin conc (mg/L)
PAEDIATRIC TEST predicted with
PAEDATRIC INDEX
10
1
1
10
Population predicted conc (mg/L)
100
100
10
1
1
10
100
Individual predicted conc (mg/L)
Patient averaged
prediction error:
Patient averaged individual
prediction error:
9.2%(-5.2,23.6)
3.9%(1.7,6.2)
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
335
330
325
Test OFV
320
Paediatric Index
315
Pooled Index
310
NWPRIOR Index
TNPRIOR Index
305
300
295
290
0
20
40
60
80
Number of children in index dataset
100
120
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:
2. Paeds:
3. NWPRIOR:
4. Pooled:
227.0
254.5
332.8
368.1
OFV of Paediatric Test Data versus Number of Children in Index Data
335
330
325
320
Test OFV
•
Paediatric Index
315
Pooled Index
310
NWPRIOR Index
TNPRIOR Index
305
300
295
290
0
20
40
60
80
Number of children in index dataset
100
120
Results
Final Model
• Pooled paediatric INDEX and TEST:
All Paediatric Data Individual Predictions versus
Observations (log scale)
All Paediatric Data Population Predictions versus
Observations (log scale)
100
Observed tobramycin conc (mg/L)
Observed tobramycin conc (mg/L)
100
10
1
10
1
0
0
0
1
10
Population predicted tobramycin conc (mg/L)
100
0
1
10
Individual predicted tobramycin conc (mg/L)
100
Results
All Paediatric Data Conditional Weighted Residual
Error versus Population Predictions
5
5
4
4
3
3
2
2
1
1
0
-1 0
14
CWRES
CWRES
All Paediatric Data Conditional Weighted Residual
Error versus Time After Dose
0
-1 0
-2
-2
-3
-3
-4
-4
60
-5
-5
Time after dose (hr)
Population predicted tobramycin conc (mg/L)
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
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•
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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(s2) = s2 (2/(N-1))½
s2 = variance (ETA)
N = DOF
CrCl Estimation from SeCr
• Aarons used Cockroft Gault:
= 150-age*wt
SeCr
(+/-10% m/f)
• “Anderson Holford” in children
= CPR
SeCr
Results