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Dear All,
I am doing the Allometric scaling of an NCE. I am able to predict the
human parameters like Vd and CL with good Regression (0.9899 and 0.9587
respectively).
Whereas I could not predict the K01 with good regression by using Brain
Weight or other normal correction factors.
But when I used GFR as a correction factor my Regression and the slope
value has increased much(0.9587 and 1.008 respectively).
Could I use these correction factors which are totally related to
excretion to predict Absorption rate constant?
Thanks in advance,
Vinu,
DMPK.
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The following message was posted to: PharmPK
Dear Vinu:
with a slope value of 1.008, have you determined whether the 95%
confidence interval of the slope estimated value includes 1?
Take care.
Tomas.
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The following message was posted to: PharmPK
vinu ca menon wrote:
> Dear All,
>
> I am doing the Allometric scaling of an NCE. I am able to predict
the
> human parameters like Vd and CL with good Regression (0.9899 and
0.9587
> respectively).
> Whereas I could not predict the K01 with good regression by using
Brain
> Weight or other normal correction factors.
Vinu,
Allometric scaling of Vd and CL has good theory and experimental data
to support the theory i.e. allometric exponents of 3/4 on Cl and 1 on
Vd (see West et al. 1997,1999).
There is no theoretical reason to suppose that brain weight is related
to either of these whole body parameters except that brain weight is
related to total body weight and therefore will be indirectly
correlated via allometric theory. I consider the use of brain weight to
be an abnormal method rather than normal.
> But when I used GFR as a correction factor my Regression and the
slope
> value has increased much(0.9587 and 1.008 respectively).
> Could I use these correction factors which are totally related to
> excretion to predict Absorption rate constant?
The absorption rate constant is a complex parameter. From the simplest
perspective it can be thought of as a reflection of the gut
permeability constant. This would be expected to be independent of body
size and so there is little reason to use allometric relationships to
explain between subject variability. You may find empirical assocations
with other covariates such as GFR but you should be cautious about
accepting them if you do not have a good mechanistic/biological reason
to explain how they are helpful.
The benefit in terms of improving the predictability of concentration
profiles in other subjects is usually negligible when based on such
empirical 'discoveries'. From a practical perspective in humans the
main demographic covariates are weight and renal function (e.g. Mould
et al) followed by age (in the very young) (e.g. Anderson et al) and
then genetic polymorphisms (in no more than half the population -- by
definition).
I would also caution you against ever using the correlation coefficient
as a measure of goodness of fit. It is notoriously affected by outliers
and can give high correlations when it is obvious from looking at a
graph of the observed and predicted values that the fit is poor. You
should consider using the objective function (e.g. weighted sum of
squares, log likelihood) to guide model building and confirm your final
choice with some kind of predictive check (see Yano et al).
Nick
West GB, Brown JH, Enquist BJ. A general model for the origin of
allometric scaling laws in biology. Science 1997;276:122-26.
West GB, Brown JH, Enquist BJ. The fourth dimension of life: fractal
geometry and allometric scaling of organisms. Science
1999;284(5420):1677-9
Mould DR, Holford NH, Schellens JH, Beijnen JH, Hutson PR, Rosing H, et
al. Population pharmacokinetic and adverse event analysis of topotecan
in patients with solid tumors. Clinical Pharmacology & Therapeutics.
2002;71(5):334-48.
Anderson BJ, van Lingen RA, Hansen TG, Lin YC, Holford NHG.
Acetaminophen developmental pharmacokinetics in premature neonates and
infants: a pooled population analysis. Anesthesiology
2002;96(6):1336-45
Yano Y, Beal SL, Sheiner LB. Evaluating pharmacokinetic/pharmacodynamic
models using the posterior predictive check. J Pharmacokinet
Pharmacodyn 2001;28(2):171-92
--
Nick Holford, Dept Pharmacology & Clinical Pharmacology
University of Auckland, 85 Park Rd, Private Bag 92019, Auckland, New
Zealand
email:n.holford.at.auckland.ac.nz tel:+64(9)373-7599x86730 fax:373-7556
http://www.health.auckland.ac.nz/pharmacology/staff/nholford/
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Copyright 1995-2010 David W. A. Bourne (david@boomer.org)