Back to the Top
Dear Colleagues,
I am a Ph.D. student trying to design and validate a physiologically based
pharmacokinetic-pharmacodynamic model following inhaled/intracheal
administration in rat, monkey, or any another species, as well as in humans
to be extrapolated to human and pathological disease state, i.e. asthma
and/or cystic fibrosis.
However I am having difficulty finding the relevant data for the model
building methodology.
Does any one have or know where I can find raw data of the following:
Drug concentrations/amounts in blood, lung and any other organs, and any
related pharmacodynamic data for the following groups of drugs, following
intratracheal/inhaled administration:
Glucocorticoids: Budesonide, Fluticasone Propionate,
Aminoglycosides: Gentamicin, Tobramycin, etc
Any assistance would be greatly appreciated
J. Emelogu
Dear Colleagues,
I am a Ph.D. student trying to design and validate a physiologically
based pharmacokinetic-pharmacodynamic model following
inhaled/intracheal administration in rat, monkey, or any another
species, as well as in humans to be extrapolated to human and
pathological disease state, i.e. asthma and/or cystic fibrosis.
However I am having difficulty finding the relevant data for the model
building methodology.
Does any one have or know where I can find raw data of the following:
Drug concentrations/amounts in blood, lung and any other organs, and
any related pharmacodynamic data for the following groups of drugs,
following intratracheal/inhaled administration:
Glucocorticoids: Budesonide, Fluticasone Propionate,
Aminoglycosides: Gentamicin, Tobramycin, etc
Any assistance would be greatly appreciated
J. Emelogu
Back to the Top
[Two 'replies' - db]
Date: Fri, 15 Jan 1999 23:49:00 -0500
From: jliu
X-Accept-Language: en
MIME-Version: 1.0
To: PharmPK.-at-.pharm.cpb.uokhsc.edu
Subject: Re: PharmPK Pharmacokinetic data
You are asking too much. If someone has all these raw data, why bother you
to build a model?
---
X-Originating-IP: [202.54.84.179]
From: "LAXMIKANT SUGANDHI"
To: PharmPK.-a-.pharm.cpb.uokhsc.edu
Subject: Re: PharmPK Pharmacokinetic data
Date: Sat, 16 Jan 1999 02:53:04 PST
Mime-Version: 1.0
this question is troubling me for a long time
please mail if u get
thanks in anticipation
l.p.sugandhi
Back to the Top
Daer colleague,
In our study:
Durisova M., Dedik L., Balan M.: Bull. Math. Biol., 57,
1995, 787-808,
we presented a new method (based on a combination of system modeling
in the frequency and time domain)
for building structured models permitting
physiological interpratation. We used this mothod in the study
of the system describing gentamicin bioavailability after
intratracheal administration in guinea pigs. The model selected
in this study indicated
four fractions of gentamicin with different pahtways
into the blood circulation. Furthermore, the model
allowed to quantify these fractions
and to determine the values of the mean resindence time corresponding
to these fractions.
The method presented in our study metioned above
can be used without any a priori information or assumptions
(e.g. those typical for compartment models), utilizing exclusively
a posteriori knowledge about the system under study provided
by experimental measurements.
However, if a priori information about the system under study
is available it can be used in this method. Except for
linearity the method is totally independent.
If you are interested in this method or in the experimental
data, do not hesitate and let me know.
Sincerely,
Maria Durisova
Back to the Top
> Hi, would you please to give me the detail method? Thanks.
O.K.
A short description of the basic steps of the method based on
a combination of system modeling in the frequency and time
domain, used in our study Durisova M., Dedik L., Balan M.,
Bull. Math. Biol., 57, 1995, 787-808, is as follows:
1. System definition.
The system describing gentamicin bioavailability after
intratracheal administration to guinea pigs (thereafter the
system) was defined by the output/input form of its transfer
function H(s)
H(s)=C_it(s)/C_iv(s),
using the deterministic circulatory model presented in our
study (Comput. Meth. Programs Biomed., 51, 1996, 183-192).
C_it(s) and C_iv(s) were the Laplace transforms of the
gentamicin concentration profiles in plasma C_it(t) and
C_iv(t) after intratracheal and intravenous administration,
respectively.
2. System modeling in the frequency domain.
The software package CXT described in our study (Int. J.
Bio-Med. Comput., 39, 1995, 231-241) was used to model the
system in the frequency domain and to obtain the inverse
transformations of the results in the time domain.
The model obtained in the frequency domain and the model
weighting function determined in the time domain indicated
the presence of time delays in the system. With the regard to
these results, the whole frequency band of the frequency
domain model was separated into the two bands: 1) the
low-frequency band in which the influences of system time
delays could not be identified by the naked eye; 2) the
high-frequency band in which these influences were distinct.
In the low-frequency band, the system was approximated by
various low-order auxiliary models without time delays, using
the CXT program.
The auxiliary models whose outputs were similar to the measured
output of the system (i.e. C_it(t) profile) were considered
the suitable auxiliary models of the system in this frequency
band. In the high-frequency band, the system time delays were
estimated.
3. System modeling in the time domain.
Various structured models with different arrangements of the
suitable auxiliary models selected in the low-frequency band
and the models containing the time delays estimated in the
high-frequency band were created and described by sets of
differential equations. Outputs of these models were obtained
as their responses to the measured input of the system (i.e.
C_iv(t) profile), by fitting these models to the measured
output of the system (i.e. C_it(t) profile), using the
Gauss-Newton method. Weighting functions of the structured
models were determined as responses of these models to the Dirac
delta pulse. Eventually, a group of the structured models was
selected in which all the models had the estimates of the
standard errors of their parameters less than 50% of the
corresponding parameter estimates, and simultaneously the
outputs and weighting functions of these models were similar
to the output and weighting function of the model determined
in the frequency domain (see step 2). The structured model
with the minimum value of the Akaike criterion was selected
in this group and considered the final structured model of
the system.
4. Determination of MRTs.
The transfer function of the final structured model was
derived using the system approach rules in the Laplace
domain. This transfer function subsequently was used to
derive the formulae for MRTs. Employing these formulae and the
parameter estimates of the final structured model, the MRTs
were determined.
Best regards,
Maria Durisova
PharmPK Discussion List Archive Index page
Copyright 1995-2010 David W. A. Bourne (david@boomer.org)