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How to calculate Ka value for a drug that is showing first order
absorption process, one compartment kinetics when administered
orally, but showing multicompartment kinetics when administered as
i.v. bolus at same dose?
SK.ABDUL MOHAMMED JAFAR SADIK BASHA
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Hello,
Ideally you could model PO and IV data simultaneously using a 2-comp
model. Usually you see this type of behaviour when absorption process is
slower than the distribution process. On the other hand, you could get your
disposition model from the IV data and deconvolve the PO data to obtain ka
(you do not need to assume first-order absorption a priori).
Regards,
Joga Gobburu
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The following message was posted to: PharmPK At 08:28 AM 8/28/02,
Abdul Mohammed Jafar Sadik Basha wrote:
>How to calculate Ka value for a drug that is showing first order
>absorption process, one compartment kinetics when administered
>orally, but showing multicompartment kinetics when administered as
>i.v. bolus at same dose?
>
This implies that Ka has a single value for a drug, which is simply
not true. See other posts here for a more complete discussion.
The use of a single value for Ka ignores so many factors that cause
the absorption rate to change with time and location. It is an
approximation that you can sometimes get away with, but it is as
limited as assuming that all drugs always have one-compartment
pharmacokinetics and are always cleared at a constant rate. Many, of
course, have multi-compartment pharmacokinetics and their clearance
is saturable.
We do not recommend using constant Ka absorption models except under
the rare conditions that the drug is highly soluble, very rapidly
absorbed in the upper small intestine, and has no saturable effects
of any kind.
Walt Woltosz
Chairman & CEO
Simulations Plus, Inc. (SIMU)
1220 W. Avenue J
Lancaster, CA 93534-2902
U.S.A.
http://www.simulations-plus.com
E-mail: walt.at.simulations-plus.com
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Dear Joga and All:
About bioavailability, and simultaneous IV and PO regimens. You
can also take subjects that have received both IV and PO dosage regimens
and estimate, for example, Ka, Fa, V, and Kel, and also Kcp and Kpc for a
peripheral compartment if desired. The USC*PACK software does that with our
population modeling software, both with the parametric iterative 2 stage
Bayesian IT2B (FOCE) and the nonparametric NPAG software. What is needed is
that each subject or patient receive the dosage by both routes in a single
overall dosage history. For example, it can be intermixed IV and PO, or
first IV then PO, or vice versa, ad lib.
If you would like to compare the behavior of the nonparametric
NPAG population modeling approach with that of the parametric IT2B
approach, which uses the FOCE approximation to the likelihood, the
performance of the IT2B with the FOCE and the NPAG is examined, for a
carefully simulated population of 800 subjects, where the parameter
distributions were in fact very Gaussian. Both approaches were compared by
Bob Leary at the San Diego Supercomputer Center with respect to
mathematical consistency (the results should get closer to the true results
as the number of subjects in the population increases), efficiency, and
convergence (how many times the original number of subjects are needed to
achieve twice the precision of parameter estimates (half the SD, for
example). Theoretically, 4 times the number are required for half the SD.
This is true for NPAG, but with the FOCE approximation, 16 times the number
are required. There is general agreement that NP methods are better when
the parameter distributions are not Gaussian. Here though, even when the
parameter distributions are specifically defined to be Gaussian, the
performance of NPAG was consistent, was more efficient, and had better
convergence than the parametric method with the FOCE approximation. Look on
our web site (www.lapk.org) under New Advances in Population Modeling.
At any rate, both methods will let you estimate Fa when the
subjects receive an intermixed regimen. For this purpose, I would be
inclined to use a consistent and efficient method with good convergence
properties.
Very best regards,
Roger Jelliffe
Roger W. Jelliffe, M.D. Professor of Medicine,
Division of Geriatric Medicine,
Laboratory of Applied Pharmacokinetics,
USC Keck School of Medicine
2250 Alcazar St, Los Angeles CA 90033, USA
email= jelliffe.at.usc.edu
Our web site= http://www.lapk.org
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The first procedure to do this could be graphically (as we did 20 years
ago):
- draw the concentrations using a semilogaritmic scale (conc is
log-scaled)
- do an regression of the elimination phase (by a ruler and a pencil)
- 'extrapolate' the elimination phase to time zero (draw the regression
line to the conc scale)
- draw the differences (d) between line and measured concentrations for
all the samples from zero to the maximum concentration
- the new points (d) show the rate of the absorption; use a regression
of this points, the slope is ka
Best regards,
Willi
Willi Cawello, PhD
Senoir Scientist Pharmacokinetics
SCHWARZ BIOSCIENCES GmbH
Alfred Nobel Str. 10
D40789 Monheim am Rhein, Germany
willi.cawello.-at-.schwarzbiosciences.com
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