Back to the Top
[Originally from "Joan Garrell"
I have just arrived to PK field, working in preclinical studies. I am
trying to manage data and statistics when comparing bioavailability data
obtained from independent animals (one point, one animal). I have only
found a method of calculating and comparing AUC obtained in this way
from Shoenwald et al. I'd apreciate any help in how to deal with
statistics in bioequivalence studies when a curve is obtained from
different animals ending with a curve made of medium values but not a
'medium curve'
Thanks in advance
Carmen
David Bourne, Ph.D., OU HSC College of Pharmacy, Oklahoma City, OK 73117
Voice: (405) 271-6481 FAX: (405) 271-3830
Internet: david-bourne.at.uokhsc.edu OR david.-at-.pharm.cpb.uokhsc.edu
OUHSC College of Pharmacy WWW server: http://www.cpb.uokhsc.edu/
VL Pharmacy Page http://www.cpb.uokhsc.edu/pharmacy/pharmint.html
LISTSERVs PharmMM.-at-.pharm.cpb.uokhsc.edu (Pharmacy Teaching)
PharmPK.aaa.uokhsc.edu (PK/PD Issues)
PharmPC.-at-.pharm.cpb.uokhsc.edu (P'ceutic/Analysis Issues)
Back to the Top
Re: calculation of bioavailability one point per animal...
Carmen-
Was each animal given the same dose and was that dose expressed per kg body
weight?
Were data collected after both intravenous and oral doses or did you use
some relative
standard?
What are the units of measurement of your individual data samples? Do you
have body
weights or plasma volumes for the individual animals?
Unless all the animals are the same or nearly the same size, it may be
useful to
normalize the data set before calculating the AUC. If the dose was given
per kg, this
normalization may already be built into your data set.
You can assign statistical weight to the data based on your knowledge of the
measurement error. Then you can fit the data to a sum of exponentials, or to a
compartmental model, or use a "noncompartmental" approach as described by
(for example)
Gibaldi, M., Biopharmaceutics and Clinical Pharmacokinetics, 4th ed., Lea
and Feibiger,
1991.
As with all AUC measurements, you will have to choose some estimate of the
slowest
exponential to extrapolate to t= infinity. For this reason, it is always
desirable to
have data as far out in time as possible.
Now, when you do your least squares fit you will get point estimates for
your AUCs and
you will get coefficients of variation based on your estimate of
measurement error. For
this part of the work, my favorite software is SAAM II, but there are many
other
capable packages.
Good luck and post again if this doesn't help.
Regards,
Bob
--
Robert D Phair PhD: rphair.-a-.ix.netcom.com
BioInformatics Services: http://www.webcom.com/rphair
Partnering and Outsourcing for Computational Biology
Back to the Top
Recent article by Ette et al. (J. Pharmacokinet. Biopharm. 1995, 23:
551) may help.
--
--------
Vladimir Piotrovskij, Ph.D. Fax: +32-14-603768
Janssen Research Foundation Email: vpiotrov.aaa.janbe.jnj.com
Clinical Pharmacokinetics
B-2340 Beerse
Belgium
from: "Vladimir Piotrovskij"
Want to post a follow-up message on this topic?
If this link does not work with your browser send a follow-up message to PharmPK@lists.ucdenver.edu with "PK preclinical" as the subject | Support PharmPK by considering my eBooks |
Copyright 1995-2014 David W. A. Bourne (david@boomer.org)