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Hello,
Present time, I'm working with coordination compound of Germanium with =
biolegandes (Nicotinic acid, Nicotinamide and Succinic acid). I have =
calculated already pharmacokinetics data for onecompatmental analysis =
and now I'm looking for program for twocompartmental analysis.
Any recommendation will much appreciated.
Katerina Shemonayeva
Odessa state medical university (Ukraine)
Department general pharmacology
Shemonayev.-at-.farlep.net
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Dear Katerina,
WinNonlin is a state-of-the-art pharmacokinetics software package that
offers the functionality you describe. The software includes a pre-written
library of Pharmacokinetic and Pharmacodynamic models, including 1- and 2-
compartment PK models for IV bolus, IV infusion, and extravascular (1st
order absorption) data. Three compartment IV bolus and infusion models are
also included in the library.
If the model of interest is not included in our pre-built library of models,
you have the freedom to write your own model using WinNonlin's native
modeling language. Alternatively, models may also be written and compiled
in either FORTRAN or C++.
We offer a number of programs whereby users at academic institutions may
obtain copies of our software at substantially reduced prices, or in some
cases, at no charge at all. To inquire about these opportunities, please
contact our sales team at sales.-a-.pharsight.com.
Please let me know if you have any questions, or if there is some way that I
may be of further assistance.
With Best Regards,
Mark R. Lovern, Ph. D.
Pharsight Scientific Support
Phone: +44 (0) 208 323 8402
Mobile: +44 (0) 781 243 0555
FAX: +44 (0) 208 323 8415
Argentum Center
2 Queen Caroline Street
London, England W6 9DX
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The following message was posted to: PharmPK
Katerina,
An option to fitting simple compartments is to calculate pharmacokinetic
parameters using noncompartmental or model-independent methods. The best
and most comprehensive example of this approach is PK Solutions, which
produces some 75 pharmacokinetic results with a few mouse clicks.
You are invited to get a demo of PK Solutions and a free summary of
pharmacokinetic equations from http://www.SummitPK.com
Regards,
David
David S. Farrier, Ph.D. Phone: 970-249-1389
Summit Research Services Fax:: 970-249-1360
68911 Open Field Dr. Email: DFarrier.aaa.SummitPK.com
Montrose, CO 81401 Web: http://www.SummitPK.com
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[One reply and a note regarding a virus alert false alarm - db]
From: Nick Holford
Date: Wed, 26 Sep 2001 11:15:47 +1200
To: david.-at-.boomer.org
Subject: Re: PharmPK Re: Pharmacokinetic software search
The following message was posted to: PharmPK
"David S. Farrier (by way of David Bourne)" wrote:
> An option to fitting simple compartments is to calculate pharmacokinetic
> parameters using noncompartmental or model-independent methods.
What do you mean by "model-independent" methods? The
non-compartmental approaches for estimation of clearance and Vss
model-dependent (i.e. they assume first-order elimination from a
central compartment). Estimation of terminal half-life assumes a
log-linear model which is equivalent to the first-order assumption.
--
Nick Holford, Divn 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)373-7599x6730 fax:373-7556
http://www.phm.auckland.ac.nz/Staff/NHolford/nholford.htm
---
From: "David S. Farrier"
Date: Tue, 25 Sep 2001 18:13:16 -0600
To: david.-a-.boomer.org
Subject: Re: PharmPK Pharmacokinetic software (NOTE)
The following message was posted to: PharmPK
***False Alarm***
Earlier today, I sent the message below to the PharmPK list. Two people
called to tell me that they received a virus warning when they accessed our
www.SummitPK.com site. This was a false alarm and has been corrected. The
web site is clean and is inspected daily by web hosting personnel.
Apparently a short JavaScript section included in the source HTML code that
scrolls text in the status bar triggered the alert. The script has been
there for 4 years, but we removed it anyway.
Use of JavaScript is quite common and I am sure we will all see a lot more
false alarms until the anti-virus definition for the Nimbda worm is made
more specific.
In sum, if you got a warning, it was a false alarm! The site is clean,
always was and always will be. So go have a look at the PK toys and software.
Thanks
David S. Farrier, Ph.D.
Director, Summit Research Services
http://www.SummitPK.com
DFarrier.at.SummitPK.com
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Nick,
It seems that Gibaldi and Perrier (Pharmacokinetics, 2nd ed., Marcel
Dekker, 1982) wrestled with the same semantics. On page 409 of their
classic text, they referred to "non-compartmental methods" as usually based
on AUC information. But it is evident from their treatment of the sum of
exponential terms describing conc-time data that this approach also fits
under the umbrella of "noncompartmental" approaches.
"Model-independent" and "noncompartmental" are seemingly synonymous, both
implying that the math is based on something other than curve fitting to
find a best fit for a presumed compartmental model. Yet, as you point out,
even area measurements, if they are carried to infinity, or the mere
calculation of a half life both assume linear first order kinetics, which
in turn implies a simple one-compartment model, at least.
Perhaps "model-independent" and "noncompartmental" are really used by most
people to imply calculation methods that are based on something other than
applying curve-fitting procedures to find the best compartmental match for
the data.
Again on page 409, Gibaldi and Perrier made this point: "Noncompartmental
methods do not require the assumption of a specific compartmental model for
either drug or metabolite. In fact, these methods can be applied to
virtually any compartmental model, provided that we can assume linear
pharmacokinetics [re: your observation]. Noncompartmental methods are
hardly new. However, the idea that noncompartmental methods provide a
general approach for pharmacokinetic analysis is both new and important.
During the preparation of this edition of "Pharmacokinetics" [book title],
there has been a distinct shift away from computer-based curve-fitting of
experimental data and elaboration of compartmental models and towards
noncompartmental methods of analysis."
Hence, PK Solutions has succeeded in encapsulating the breadth of Gibaldi
and Perrier's exponential terms and area calculation approaches to provide
some 75 pharmacokinetic parameters based on "noncompartmental" methods,
while leaving it to WinNonLin and other software to advance the
compartmental curve-fitting approach.
A survey of the literature shows that most papers on general
pharmacokinetics tabulate parameters arrived at by noncompartmental
methods, not to minimized the importance of curve-fitting to compartmental
models, when needed. Since PK Solutions produces more noncompartmental
parameters from a set of blood level data than any software available, we
like to quote one of our customers who put it this way:
"PK Solutions fills the gap for noncompartmental pharmacokinetic analysis."
I think the distinction between noncompartmental and compartmental
approaches is important to keep in mind. So thanks for the opportunity to
enter the fray. Perhaps others will want to make a new thread on this topic.
Warm Regards,
David
David S. Farrier, Ph.D. Phone: 970-249-1389
Summit Research Services Fax:: 970-249-1360
68911 Open Field Dr. Email: DFarrier.aaa.SummitPK.com
Montrose, CO 81401 Web: http://www.SummitPK.com
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The following message was posted to: PharmPK
"David S. Farrier (by way of David Bourne)" wrote:
> An option to fitting simple compartments is to calculate pharmacokinetic
> parameters using noncompartmental or model-independent methods.
What do you mean by "model-independent" methods? The
non-compartmental approaches for estimation of clearance and Vss
model-dependent (i.e. they assume first-order elimination from a
central compartment). Estimation of terminal half-life assumes a
log-linear model which is equivalent to the first-order assumption.
--
Nick Holford, Divn 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)373-7599x6730 fax:373-7556
http://www.phm.auckland.ac.nz/Staff/NHolford/nholford.htm
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The following message was posted to: PharmPK
Dear Dr. Farrier,
I don't have a comment on your statements about
noncompartmental pharmacokinetics, in your reply to Dr. Holford.
However, I have some comments on what you did not say.
What is the use of noncompartmental PK? You are right that it can
produce a lot of numbers, similarly to compartmental PK, but with
less assumptions. That's OK. But PK is more than producing
numbers. In many cases we want to make a prediction of the time
course of plasma concentration profile, eg. for dosage regimen
calculation. Data from noncompartmental modeling can be used to
determine the dosing rate for maintaining a steady state
concentration (in case of iv infusion) or an average concentration (in
case of multiple dosing with equal intervals). But what more can be
predicted from noncompartmental PK data? How about the dosing
interval and prediction of peak and trough levels?
In my view, noncompartmental PK is useful only in cases where
the data do not allow compartmental PK, and in such cases the
credibility of the data may be questionable.
Any comments to these somewhat provoking statements are
welcomed.
Best regards,
Hans Proost
Johannes H. Proost
Dept. of Pharmacokinetics and Drug Delivery
University Centre for Pharmacy
Antonius Deusinglaan 1
9713 AV Groningen, The Netherlands
tel. 31-50 363 3292
fax 31-50 363 3247
Email: j.h.proost.at.farm.rug.nl
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[A few replies - db]
From: "Gobburu, Jogarao V"
Date: Sat, 29 Sep 2001 13:18:32 -0400
To: david.aaa.boomer.org
Subject: RE: PharmPK Re: Pharmacokinetic software search
Status: R
The following message was posted to: PharmPK
Dear Dr. Proost,
In my opinion, both noncompartmental (NCA) and compartmental (CA) methods
are almost inevitable for any given problem. I would not take the stand that
NCA should ONLY be used when CA fails. Firstly, if we have observational
data, it is impossible to analyse the data without some prior knowledge. Let
us focus on experimental data, which I think is more relevant to this
discussion. As we all might appreciate, for nonlinear regression initial
estimates are critical. The only method to obtain reasonable initial
estimates is indeed NCA. One might do it formally or informally by
eye-balling, nevertheless we all do it. At the same time, we all, probably
appreciate the fact that CA offers a very powerful advantage over NCA -
generalizability.
Regarding dosing interval calculations, I think we should also take into
account the pharmacodynamics and disease progression. Hence it is a more
complicated issue and CA is inevitable.
My previous comment about initial estimates holds good for PD too.
Regards,
Joga Gobburu,
Pharmacometrics,
CDER, FDA
---
From: Roger Jelliffe
Date: Sat, 29 Sep 2001 12:49:23 -0700
To: david.-a-.boomer.org
Subject: Re: PharmPK Re: Pharmacokinetic software search
Status: R
Dear Dr. Proost:
Thanks for your comments on noncompartmental analysis. I
agree with you 100%.
Very 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.aaa.hsc.usc.edu
Our web site= http://www.usc.edu/hsc/lab_apk
---
From: "David S. Farrier"
Date: Sun, 30 Sep 2001 00:54:36 -0600
To: david.aaa.boomer.org
Subject: Re: PharmPK Re: Pharmacokinetic software search
Status: R
Johannes,
Thank you for your viewpoint. I did not mean to become the
protagonist for "noncompartmental" pharmacokinetics, but I will, if
elected. I sometimes ponder how significant it is to define a
compartment, the physiological significance of which is astutely
denied. Compartments seem forever "theoretical".
Our goal at SummitPK.com was not to take sides, but to help the sides
taken. Once, I tabulated the types of parameters reported and the
calculation methods employed by authors off "pharmacokinetics" papers
in the Journal of Pharmacy and Drug Metabolism and Disposition during
the five year period of 1992-1997. I discovered that 99% of the
papers used "noncompartmental" methods to report a set of some 10-20
common PK parameters deemed sufficient (by authors and peer reviews
alike) to described the pharmacokinetics of a drug. Interestingly,
there was no consensus of software employed. Most authors admitted to
using ad hoc spreadsheet calculation.
That is when we decided that the goal of PK Solutions was to provide
a set of noncompartmental results that would have served all those
authors over 5 years of published articles in two journals as the
only software needed to publish their papers.
Strict compartmental analysis is definitely useful, but by the looks
of it, only to a few.
Respectfully,
David S. Farrier
http://www.SummitPK.com
The place where you can find a great noncompartmental PK analysis
program for pros and novices alike.
David S. Farrier, Ph.D. Phone: 970-249-1389
Summit Research Services Fax:: 970-249-1360
68911 Open Field Dr. Email: DFarrier.aaa.SummitPK.com
Montrose, CO 81401 Web: http://www.SummitPK.com
---
From: "Stephen Duffull"
Date: Mon, 1 Oct 2001 12:53:15 +1000
To: david.-a-.boomer.org
Subject: RE: PharmPK Re: Pharmacokinetic software search
Status: R
The following message was posted to: PharmPK
Hi
Just a comment to agree with Hans and to comment on one of his points...
> say. What is the use of noncompartmental PK? You are right
> that it can produce a lot of numbers, similarly to
> compartmental PK, but with less assumptions.
It is a common assumption that non-compartmental PK has less
assumptions. I'm not convinced that this is true at all. It is not
really "non-compartmental" since it requires the underlying
"compartmental" model to fulfil certain characteristics for AUC and CL
to retain their meaningful relationship (see Nicks previous comment)
[this is a circular problem]. I prefer to use the term "non-parametric"
PK. Non-parametric PK provides a summary of the outputs of a PK system
(similar to non-parametric statistics).
However if the observations are not close to the time of the "true"
Cmax, or the Cmin was poorly quantified, or the log-linear portion of
conc-time curve poorly characterized, or there are non-linearities in
the system, or the actual sampling time differs significantly from the
nominal sampling time then our estimates of Tmax, Cmax, AUC, AUMC,
tz(1/2), MRT etc etc will have significant error in them. Since these
non-parametric PK metrics are only of use for descriptive (rather than
predictive) purposes then do they really have less assumptions than a
model used for descriptive purposes only? Indeed one could go so far as
to develop an empirical model (eg sum of exponentials) and the
non-parametric PK metrics calculated from the model predicted
obervations rather than the actual observations [now this is getting
very circular]...
I wonder, if non-parametric PK were compared to parametric PK for
descriptive purposes that the "lack of assumptions" would indeed be
superior... [I personally doubt it]
Kind regards
Steve
Stephen Duffull
School of Pharmacy
University of Queensland
Brisbane, QLD 4072
Australia
Ph +61 7 3365 8808
Fax +61 7 3365 1688
http://www.uq.edu.au/pharmacy/duffull.htm
---
From: exfamadu.-a-.savba.sk
Date: Mon, 1 Oct 2001 15:08:48 +0200
To: david.-at-.boomer.org
Subject: Re: PharmPK Re: Pharmacokinetic software search
The following message was posted to: PharmPK
Data from noncompartmental modeling can be used to
> determine the dosing rate for maintaining a steady state
> concentration (in case of iv infusion) or an average concentration (in
> case of multiple dosing with equal intervals). But what more can be
> predicted from noncompartmental PK data? How about the dosing
> interval and prediction of peak and trough levels?
Dear Dr. Proost,
In our study:
Dedik L., Durisova M., Batorova M.: Weighting function used for
adjustment of multiple-bolus drug dosing, Meth. Find. Exp. Clin.
Pharmacol., 2000, 22, 543-549,
we presented utilization of results of a specific type of noncompartmental
modeling for the adjustment of the multiple-bolus dosing of a drug. This
method allows to determine patient-specific loading and maintenance
bolus doses of the drug, necessary to reach and maintain prescribed
trough levels of the drug in a patient at desired time-points, both (the levels
and time-points) specified by treatment requirements. The method is
exemplified by the adjustment of the multiple-bolus dosing of factor VIII in
treatment of hemophilia A.
With best regards,
Maria Durisova
Maria Durisova, Ph.D., D.Sc.,
Senior Research Worker and
Scientific Secretary
Institute of Experimental Pharmacology
Slovak Academy of Sciences
842 16 Bratislava
Dubravska cesta 9
Slovak Republic
Phone/Fax: 00421 2 5477 5928
http://nic.savba.sk/sav/inst/exfa/durisova.htm
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The following message was posted to: PharmPK
> From: "Stephen Duffull"
> I prefer to use the term "non-parametric"
> PK. Non-parametric PK provides a summary of the outputs of a PK system
> (similar to non-parametric statistics).
I don't agree that non-parametric is a useful term in this context.
The term non-parametric in a hypothesis testing context refers to not
requiring to assume a specific *parametric* distribution. The term
non-compartmental in a pharmacokinetic context refers to not
requiring to assume a specific *compartmental* structure.
The assumptions of NCA are similar, but more restrictive (e.g. only
linear systems make sense to estimate Vss), than compartmental
analysis.
NCA is used to predict parameters (CL, Vss, etc) so what makes it
non-parametric?
--
Nick Holford, Divn Pharmacology & Clinical Pharmacology
University of Auckland, 85 Park Rd, Private Bag 92019, Auckland, New Zealand
email:n.holford.-a-.auckland.ac.nz tel:+64(9)373-7599x6730 fax:373-7556
http://www.phm.auckland.ac.nz/Staff/NHolford/nholford.htm
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[Two replies - db]
From: "Hans Proost"
Date: Tue, 2 Oct 2001 16:42:21 MET
To: david.-a-.boomer.org
Subject: Re: Pharmacokinetic software search
The following message was posted to: PharmPK
Dear colleagues,
Thank you for the many replies to my provoking comments to
noncompartmental analysis (NCA). Actually I agree with each of
these replies, and I think that the position of NCA is somewhat
clarified.
IMHO there is at least one useful application of NCA. The
estimation of clearance (or CL/F for extravascular dosing) from
Dose/AUC is the most simple and robust method (unless a
considerable part of AUC must be obtained by extrapolation). If this
estimate of clearance differs markedly from one obtained from a
very sophisticated CA, I probably would prefer the NCA estimate.
Or perhaps better, I would prefer none of them.
With respect to terminology, the term NCA is actually broader than
I had in mind. The approach described by Dr. Maria Durisova and
colleagues is indeed NCA. As I understand, they describe drug
behavior using mathematical equations which cannot be translated
to compartmental models (i.e. not polyexponentials). This may
work, as may be concluded from their examples, but it remains
difficult, if not impossible, to understand these functions in a
physiological context. The attractive feature of compartmental
modeling is that it helps understanding what happens in the body.
For example, in case of impaired renal function, clearance may be
expected to decrease parallel with creatinine clearance, and dose
corrections can be predicted quantitatively. Such predictions under
various conditions are allowed since the compartmental modeling
has at least some physiological meaning. Of course, we should not
overinterpret the model, and we should always be aware of its
limitations. However, it makes sense.
Best regards,
Hans Proost
Johannes H. Proost
Dept. of Pharmacokinetics and Drug Delivery
University Centre for Pharmacy
Antonius Deusinglaan 1
9713 AV Groningen, The Netherlands
tel. 31-50 363 3292
fax 31-50 363 3247
Email: j.h.proost.-at-.farm.rug.nl
---
From: "Stephen Duffull"
Date: Tue, 2 Oct 2001 17:00:46 +1000
To: david.-at-.boomer.org
Subject: RE: PharmPK Re: Pharmacokinetic software search
The following message was posted to: PharmPK
Nick
> > From: "Stephen Duffull"
> > I prefer to use the term "non-parametric"
> > PK. Non-parametric PK provides a summary of the outputs of a PK
> > system (similar to non-parametric statistics).
>
> I don't agree that non-parametric is a useful term in this
> context.
That's fine - this is just terminology. We know that NCA does require
compartmental assumptions (eg linearity is an obvious one - but also it
is not appropriate to assume the AUC-CL relationship for a 2 cpt Rowland
model either...)
> The term non-parametric in a hypothesis testing
> context refers to not
> requiring to assume a specific *parametric* distribution. The term
> non-compartmental in a pharmacokinetic context refers to not
> requiring to assume a specific *compartmental* structure.
Non-parametric simply means no parameters. Whether this is for
statistics or not. NCA is a method for summarising data (ie
concentrations) into various metrics (eg Tmax, Cmax, AUC, AUMC etc).
Whether the user then wants to convert these to "parameters" from some
unknown model is their own choice. We also know that compartmental
structure needs to be assumed for NCA derived "parameters" to have
meaning. This obviously differs from the IO model where we try and
estimate models and parameters that match the inputs to the outputs (ie
a parametric PK analysis).
> NCA is used to predict parameters (CL, Vss, etc) so what makes it
> non-parametric?
It is non-parametric simply because to get the summary "statistics" of
the concentrations you do not have to have parameters. Similarly you do
not need parameters to describe a distribution of (any) data using
median or percentiles.
Cheers
Steve
Stephen Duffull
School of Pharmacy
University of Queensland
Brisbane, QLD 4072
Australia
Ph +61 7 3365 8808
Fax +61 7 3365 1688
http://www.uq.edu.au/pharmacy/duffull.htm
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[A few more replies - db]
From: "Hans Proost"
Date: Tue, 2 Oct 2001 16:42:21 MET
To: david.aaa.boomer.org
Subject: Re: Pharmacokinetic software search
Status: R
The following message was posted to: PharmPK
Dear colleagues,
Thank you for the many replies to my provoking comments to
noncompartmental analysis (NCA). Actually I agree with each of
these replies, and I think that the position of NCA is somewhat
clarified.
IMHO there is at least one useful application of NCA. The
estimation of clearance (or CL/F for extravascular dosing) from
Dose/AUC is the most simple and robust method (unless a
considerable part of AUC must be obtained by extrapolation). If this
estimate of clearance differs markedly from one obtained from a
very sophisticated CA, I probably would prefer the NCA estimate.
Or perhaps better, I would prefer none of them.
With respect to terminology, the term NCA is actually broader than
I had in mind. The approach described by Dr. Maria Durisova and
colleagues is indeed NCA. As I understand, they describe drug
behavior using mathematical equations which cannot be translated
to compartmental models (i.e. not polyexponentials). This may
work, as may be concluded from their examples, but it remains
difficult, if not impossible, to understand these functions in a
physiological context. The attractive feature of compartmental
modeling is that it helps understanding what happens in the body.
For example, in case of impaired renal function, clearance may be
expected to decrease parallel with creatinine clearance, and dose
corrections can be predicted quantitatively. Such predictions under
various conditions are allowed since the compartmental modeling
has at least some physiological meaning. Of course, we should not
overinterpret the model, and we should always be aware of its
limitations. However, it makes sense.
Best regards,
Hans Proost
Johannes H. Proost
Dept. of Pharmacokinetics and Drug Delivery
University Centre for Pharmacy
Antonius Deusinglaan 1
9713 AV Groningen, The Netherlands
tel. 31-50 363 3292
fax 31-50 363 3247
Email: j.h.proost.aaa.farm.rug.nl
---
From: Roger Jelliffe
Subject: Re: PharmPK Re: Pharmacokinetic software search
Mime-Version: 1.0
Dear All:
Let's talk a bit about the term "nonparametric". Often this
is used in place of the word "noncompartmental". However, to my
knowledge, the parameters in noncompartmental models are usually
described in terms of means and variances, with the usual implied
assumption of Gaussian or lognormal parameter distributions. Because
of this, it may nor be useful or correct to describe noncompartmental
models as being nonparametric.
The word nonparametric (NP) is also used in connection with
describing the parameter distributions in conventional compartmental
models, either linear or nonlinear. In this regard, the NP approaches
make no parametric assumptions about the shape of the distribution of
the parameters, as do the usual parametric methods, which usually
assume that the parameter distributions are either normal or
lognormal, and therefore are fully described by the parameter means
and variances that one gets. In contrast, the nonparametric approach,
first done by Alain Mallet, (nonparametric maximum likelihood - NPML)
makes no such assumptions about the shape of the parameter
distributions - the shape, whatever it is, is determined solely by
the data of doses and responses in the population. The approach finds
the distribution having the maximum likelihood given the raw data and
the weighting scheme used. Alan Schumitzky has also developed the
nonparametric expectation - maximization (NPEM) approach. They both
get basically the same results from the same raw data. More recently,
Bob Leary at the San Diego Supercomputer Center has developed the
nonparametric adaptive grid (NPAG) approach, which is considerably
more efficient and much faster, with results having greater
likelihood. All these methods are examples of nonparametric analysis
of models which rave definite structure, usually compartmental
models. They are designed to find the most likely parameter
distributions given the raw data. Usually, the likelihood obtained by
the nonparametric methods is greater that that seen with parametric
methods, as they are designed to exactly that, unconstrained by any
assumptions of normality or lognormality or anything like that. In
addition, the NP methods are mathematically consistent. They have the
property that the more you sample from a population, the more closely
the results approach the true results in the population. Parametric
methods may have smaller population coefficients of variation about
the population parameter means. Usually the results are less likely,
though, as they are constrained by the assumed shape.
David Bourne, if you will accept an attachment to this
message, I will attach a powerpoint file for a recent roundtable
discussion, which describes this a bit more for those who are
interested, in the context of optimal individualized drug therapy for
which the population models provide the framework (the Bayesian
prior) for planning the optimal initial dosage regimen.
[Sorry Roger no attachments...in this case especially it seems to be
too big - db]
Notice also, that when one uses Bayes' theorem to get
Bayesian posteriors from the measured responses or concentrations,
that you then get a nonparametric Bayesian posterior joint density.
The new method of "multiple model" dosage design is then specifically
designed to achieve target goals with maximum precision, whether this
based on the Bayesian prior ( the NP population model) or the
posterior joint parameter density.
I look forward to discussing this more with those who are
interested. To my knowledge, these methods, based on nonparametric
models as the Bayesian prior, can develop the most precise dosage
regimens I know, for the optimal attainment of target goals, for
drugs having narrow margins of safety, where we need to have such
precision.
Best regards to all,
Roger Jelliffe
---
From: "Dr. Ibrahim Wasfi"
Subject: Re: PharmPK Re: Pharmacokinetic software search
To: PharmPK.at.boomer.org
MIME-version: 1.0
X-Priority: 3
Hans Proost wrote
"The
estimation of clearance (or CL/F for extravascular dosing) from
Dose/AUC is the most simple and robust method (unless a
considerable part of AUC must be obtained by extrapolation"
Could you please be specific ( percentage ! ) about " unless a considerable
...."
Regards,
Ibrahim A. Wasfi
Forensic Science Laboratory
P O Box 253, Abu Dhabi
United Arab Emirates
Tel + 4092522
Fax + 4463470
---
From: exfamadu.-a-.savba.sk
Date: Thu, 4 Oct 2001 11:40:18 +0200
To: david.-a-.boomer.org
Subject: Re: PharmPK Re: Pharmacokinetic software search
The following message was posted to: PharmPK
Dear Dr. Hans Proost,
> With respect to terminology, the term NCA is actually broader than
> I had in mind.
There is a good paper:
K. H. Norwich: Noncompartment models of whole-body clearance of
tracers: A review, Annals of Biomedical Engineering, 25, 1997, 421-439.
> The approach described by Dr. Maria Durisova and
> colleagues is indeed NCA. As I understand, they describe drug
> behavior using mathematical equations which cannot be translated
> to compartmental models (i.e. not polyexponentials). This may
> work, as may be concluded from their examples, but it remains
> difficult, if not impossible, to understand these functions in a
> physiological context.
The models used in our work are called the transfer-function models.
Time-domain responses of these models to mathematically described
drug inputs may have the form of polyexponentials.
All the linear compartment models can be written in the form of the
transfer-function models. An example of a relationship between a
compartment model and a transfer-function model is described in detail in
our study:
M.Durisova, L.Dedik, et al., Pharmacokinetics of Factor VIII in hemophilia
A patients assessed by frequency response method, Methods and
Findings in Experimental and Clinical Pharmacology, 20, 1998, 217-
226. This study also shows examples of bio-medical purport of parameters
of transfer-function models. Other examples can be found in our other
studies.
With best regards,
Maria Durisova
Maria Durisova, Ph.D., D.Sc.,
Senior Research Worker and
Scientific Secretary
Institute of Experimental Pharmacology
Slovak Academy of Sciences
842 16 Bratislava
Dubravska cesta 9
Slovak Republic
Phone/Fax: 00421 2 5477 5928
http://nic.savba.sk/sav/inst/exfa/durisova.htm
---
From: Prah.James.aaa.epamail.epa.gov
Subject: Re: PharmPK Re: Pharmacokinetic software search
To: david.-at-.boomer.org
MIME-version: 1.0
Dr. Bourne,
Given clearance and dose by one route can dose, given AUC and clearance, be
calculated for a different route such as dermal in the same subject?
Thanks,
Jim
James D. Prah, PhD
US EPA
Human Studies Division MD (58B)
Research Triangle Park, NC, 27711
919 966 6244
919 966 6367 FAX
Back to the Top
[Two replies - db]
From: "Hans Proost"
Date: Mon, 8 Oct 2001 09:41:55 MET
To: david.at.boomer.org
Subject: Re: Pharmacokinetic software search
The following message was posted to: PharmPK
Dear Dr. Wasfi,
In reply to my comment:
> "The
> estimation of clearance (or CL/F for extravascular dosing) from
> Dose/AUC is the most simple and robust method (unless a
> considerable part of AUC must be obtained by extrapolation"
you wrote:
> Could you please be specific ( percentage ! ) about " unless a considerable
> ..."
Your question is clear, but the answer is more complicated.
Consider the following example:
The AUC from time zero until the last sampling time is 80 (arbitrary
units). If this AUC is determined using linear or log-linear
trapezoidal rule, if it is calculated from a reasonable number of
measurement (say 10 or more) that are well-spread over the time
scale, this value may be considered rather accurate. The precision
of the calculated AUC may be estimated from the measurement
error.
If the concentration at the last sampling point is not zero (if fact, it
will never be zero, but let's stay practical for this moment), then the
AUC must be extrapolated from:
AUC(t_last to infinitity) = C_last / k_terminal
where k_terminal is the estimated elimination rate constant
obtained over, say, the last four measurements.
Let us assume that the extrapolated AUC is 20. One can be sure
that this value is less precise than the AUC(0 to t_last), since it
includes the error in C_last and in k_terminal. The precision of the
extrapolated AUC may be estimated from the measurement error in
C_last and the precision (SD) of the estimated k_terminal.
Thus, the total AUC is 100, and the extrapolated part is 20% of
total AUC. In general, one may expect that the accuracy in the
total AUC is 'reasonable'. However, it should be noted that the
value '20%' is dependent on the precision of the extrapolation.
If the extrapolated part of the AUC is considerably larger than 20%,
the situation becomes much worse. Therefore, as a rule of thumb,
one should not use AUC values if the extrapolated part exceeds
20%. However, this value of 20% is rather arbitrary.
The precision of the total AUC can be estimated from the precision
of both parts of the AUC. This procedure allows a fair judgement of
the impact of the extrapolation on the reliability of the estimated
total AUC. This procedure provides a better basis for judgment than
whatever 'rule of thumb'.
I don't know the exact regulatory guidelines at this moment, but the
aforementioned reasoning may be helpful in estimating the
precision of total AUC.
Sincerely,
Hans Proost
Johannes H. Proost
Dept. of Pharmacokinetics and Drug Delivery
University Centre for Pharmacy
Antonius Deusinglaan 1
9713 AV Groningen, The Netherlands
tel. 31-50 363 3292
fax 31-50 363 3247
Email: j.h.proost.aaa.farm.rug.nl
---
From: Roger Jelliffe
Date: Mon, 08 Oct 2001 10:20:33 -0700
To: david.aaa.boomer.org
Subject: Re: PharmPK Re: Pharmacokinetic software search
Dear David:
Thanks for including my comments. Sorry you cannot include
the attachment. For those who are interested in nonparametric
population modeling, there is more material on our web site.
www.lapk.org
Most is under the heading of teaching topics.
Very best regards to all,
Roger Jelliffe
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