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Dear all,
at the moment we are working on the pharmacokinetics of an enzyme
administered in pediatric patients as a short time infusion. The
drug has 140 kDa and is supposed to be eliminated by the RES.
Regarding just one dosage we can describe the pharmacokinetic
profile of the substance by a Michaelis Menten equation (validated
by F-ratio test versus one compartment model. Half of the patient
profiles can also be described by a zero order elimination; for the
whole population we use therefore MM).
Looking at other dosages we get an adequate kinetic profile, but
Vmax and km increase with increasing dose.
How can we explain this?
Did anyone of you make similar observations with the kinetics of
other enyzmes?
Thank you for your help in advance.
Gudrun Wuerthwein
Dr. Gudrun Wuerthwein Tel.: +49 (0251) 218067
c/o Prof.Dr.J.Boos E-mail: wurthwg.aaa.uni-muenster.de
Institut fuer paediatrische Onkologie
der Westfaelischen Wilhelms-Universitaet
Albert-Schweitzer-Str.33
48149 M u e n s t e r (Germany)
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Hello,
I am assuming that you fitted each dose and each subject individually.
If that is so, I suggest you fit all doses/all subjects simultaneously
to reliably evaluate your parameter estimates. A population approach
will allow you to predict individual posthoc parameters for further
explorations. The lower doses may not reflect the full range of the
nonlinearity, hence Km and Vm might not be reliably estimated. This
should be a good starting point for further investigation.
Regards,
Joga
Joga Gobburu,
Pharmacometrics,
CDER, FDA.
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Hello as well,
I would like to second what Joga has said. It is especially
useful to see
the full shape of the parameter distributions, especially when using the
nonparametric approach to population modeling. This gets the most likely
parameter distributions, whose shape is determined only by the raw data
itself, and not by any assumed shape of the distribution stated by an
equuation with its parametric assumptions about their shape. The sequence
of first, carefully determining the assay error pattern independently
before doing anything else, then using a parametric approach to get the
remaining intraindividual variability, then putting this into a
nonparametric population model not only obtains the most likely parameter
distributions, but also permits use of this model for multiple model dosage
design, to hit desired targets with maximum precision. I am attaching two
MS Word files which discuss this in more detail for those who are
interested [Not attached via the list but could be forwarded on
request or possibly posted on-line after checking with Roger - db.
Best regards,
Roger Jelliffe
Roger W. Jelliffe, M.D. Professor of Medicine, USC
USC Laboratory of Applied Pharmacokinetics
2250 Alcazar St, Los Angeles CA 90033, USA
Phone (323)442-1300, fax (323)442-1302, email= jelliffe.-at-.hsc.usc.edu
Our web site= http://www.usc.edu/hsc/lab_apk
********
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[This is the same message sent out last weekend. I have placed the
two documents mentioned by Roger on-line at
http://www.boomer.org/pkin/subs/rj1/mathmod1.html and
http://www.boomer.org/pkin/subs/rj2/mathmod2.html - db]
Hello as well,
I would like to second what Joga has said. It is especially
useful to see
the full shape of the parameter distributions, especially when using the
nonparametric approach to population modeling. This gets the most likely
parameter distributions, whose shape is determined only by the raw data
itself, and not by any assumed shape of the distribution stated by an
equuation with its parametric assumptions about their shape. The sequence
of first, carefully determining the assay error pattern independently
before doing anything else, then using a parametric approach to get the
remaining intraindividual variability, then putting this into a
nonparametric population model not only obtains the most likely parameter
distributions, but also permits use of this model for multiple model dosage
design, to hit desired targets with maximum precision. I am attaching two
MS Word files which discuss this in more detail for those who are interested.
[Not attached via the list but could be forwarded on request or
possibly posted on-line after checking with Roger - db.
Best regards,
Roger Jelliffe
Roger W. Jelliffe, M.D. Professor of Medicine, USC
USC Laboratory of Applied Pharmacokinetics
2250 Alcazar St, Los Angeles CA 90033, USA
Phone (323)442-1300, fax (323)442-1302, email= jelliffe.at.hsc.usc.edu
Our web site= http://www.usc.edu/hsc/lab_apk
********---
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Copyright 1995-2010 David W. A. Bourne (david@boomer.org)