James,

I tried to deal with this in my previous reply. We do not differ. It is fine for me if you make the assumption that you do not know Fm and you estimate CLm/Fm and Vm/Fm. But this assumption in practice is an assumption that Fm=1 when you actually are estimating the parameters.

There are other assumptions that can be made depending on what you know.

Nick

James G Wright wrote:
Hi Nick,
You have written many things that are true, however I think we are
differing on a very essential point.

Nick Holford wrote

Everytime you use a model to describe oral PK data alone you must make an assumption about the dose that is absorbed.

You could make an assumption about this if you wanted to.  Or you can be
transparent and admit that you don't know F, and therefore are
estimating apparent parameters e.g CL/F, V/F.  Any assumption about F is
extrinsic to the model - it is not required.
This is equally true for modelling the metabolite where the fraction of
the dose that becomes metabolite is unknown - we are estimating CL/F,
V/F etc. for the metabolite.  Any assumption about F, V etc. is again
optional.

Do you agree?

Best regards, James

James G Wright PhD
Scientist
Wright Dose Ltd
Tel: 44 (0) 772 5636914


-----Original Message-----
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED]
On Behalf Of Samtani, Mahesh [PRDUS]
Sent: 10 December 2008 21:18
To: Nick Holford; nmusers@globomaxnm.com
Subject: RE: [NMusers] Simultaneous vs sequential for modeling parent
AND metabolites in pop PK

Dear Dr. Holford,
All I was suggesting was that once you have decided on which assumption
you like the most and start modeling the metabolite data then shouldn't
simultaneous modeling of the parent + metabolite be more preferable? The
model will take long run time any ways because it will be a $DES model.
By doing simultaneous modeling of the parent + metabolite you will
probably improve the parameters of the parent drug because the
metabolite information will bolster the parameters of the parent drug.
Similarly common parameters between the parent and metabolite will
benefit as well because of the simultaneous estimation.

Of course if the metabolite data is really dirty and you are really
afraid that the metabolite data will contaminate the parent drug's
parameters then that situation seems to be a reasonable place to try
sequential modeling.

Kindly advise,
Mahesh

-----Original Message-----
From: [EMAIL PROTECTED]
[mailto:[EMAIL PROTECTED] Behalf Of Nick Holford
Sent: Wednesday, December 10, 2008 3:12 PM
To: nmusers@globomaxnm.com
Subject: Re: [NMusers] Simultaneous vs sequential for modeling parent
AND metabolites in pop PK


James, Mahesh,

The "F=1 fallacy" has caused me no end of stress over the years, and
next time I may have to contend with the (almost irrefutable) argument
"but Nick Holford said it was true".

As I never said this was a fallacy I dont think you need be stressed by it. Everytime you use a model to describe oral PK data alone you must make an assumption about the dose that is absorbed. By default NONMEM will make the assumption that Foral=1 but of course when you interpret the parameters you should remember the assumption.

Similarly you may assume Fm=1 and estimate metabolite parameters of CLm/Fm and Vm/Fm where Fm is the fraction of parent converted to metabolite. For simply descriptive purposes the Fm=1 assumption is fine but more might be learned by making a different assumption (as Mahesh points out). Fm might be guessable from in vitro descriptions of metabolism or one may assume a Vm (metabolite volume) perhaps the same as the parent. The latter can aid in proposing plausible values for Fm but the descriptive value of the model is unchanged whichever assumption

is used.

I dont understand why Mahesh adds to each of the assumptions "[and preferably do simultaneous parent/metabolite modeling]". Perhaps he could give some reasons for this because I dont see it has anything to do with the choice of which assumption to make.

IMHO the important thing is to recognize that an assumption must be made. I have seen people use NONMEM to estimate Fm and CLm and Vm as if they could identify these 3 parameters independently. NONMEM will do what it is told and make estimates of the parameters even though one of them cannot be identified. This is the important lesson to learn for those who have not had experience of parent metabolite modelling with NONMEM.

I want to stick to my original assertion that PKPD and parent-metabolite

models are similar when applying a modelling strategy of either sequential or simultaneous fitting of data.

We should remember the Box aphorism "All models are wrong but some models are useful". Part of the process is modelling is to evaluate the model to see how wrong it is. The sequential then simultaneous approach can be helpful for model evaluation as described by Liping Zhang in her second paper on PKPD models.

I see no reason why this should not apply to parent-metabolite models. However, usually parent-metabolite models are simpler because commonly one has first-order kinetics and essentially immediate conversion of parent to metabolite. The implicit assumptions of complete, rapid and first-order conversion may be fine but it still sensible to look at the data to check that these assumptions are compatible with the results from a sequential model.

Nick

James G Wright wrote:
Nick Holford wrote:
Non-proportionality (aka non-linearity) of metabolite formation from parent is not really an issue. With the right design (i.e. suitable doses of parent) then this can be discovered from just giving the parent.
The key assumptions of metabolite models are about how the metabolite
is
formed - linearly or nonlinearly, from plasma or during first-pass,
immediately or not.  Making sure your assumptions are true is really
the
issue for me with any analysis.

But to really know how much of the parent is eventually transformed to the metabolite needs additional information i.e.
direct
administration of the metabolite.
Of course, if fraction formed is the parameter that you need to
estimate.
Fitting a metabolite PK model is not dependent on assuming 100%
metabolite formation from parent, as you originally stated, unless you
mislabel the parameters as actual CL, instead of CL/F.  Not knowing F
doesn't affect the application and predictive utility of the model any
more than not knowing F for the parent after oral administration.

The widespread presentation of "F=1" as an "unverifiable assumption"
causes model end-users to suspect that the assumption could in some
sense be wrong ("Aah, but how do you know F=1?"), leading to the
perception that the metabolite model is misleading and unreliable.
I think it would be helpful if you could explicitly retract your
assertion regarding the assumption "that all drug goes to metabolite".
The "F=1 fallacy" has caused me no end of stress over the years, and
next time I may have to contend with the (almost irrefutable) argument
"but Nick Holford said it was true".

Best regards, James

Mahesh wrote:

Dear NMusers,
I think in trying to generalize the case between sequential PK/PD vs. sequential parent/metabolite we maybe forgetting some PK concepts. 1) In the case of parent/metabolite modeling the metabolite data often

carries important information about the parent drug. Eg.a. If there is formation limited kinetics going on then the terminal slopes of the parent and metabolite will both be reflective of the parent's kel Eg.b. If there is severe flip-flop kinetics going on then the terminal slopes of the parent and metabolite will both be reflective of the parent drug's ka
2) There are common parameters (e.g.. k-metabolite) between the parent

and metabolite that may be estimated in a more meaningful manner using

simultaneous modeling.
Given these considerations, my guess is that simultaneous modeling of the parent and metabolite maybe more scientifically useful (use all the information to get the best parameter estimates). On a related note; it is generally well known that if you administer only the parent and measure parent & metabolite then the volume of metabolite is not identifiable. In this case there are 3 options: a) Fix the metabolite volume to that of the parent [and preferably do simultaneous parent/metabolite modeling] b) Use prior knowledge to assign a fixed fraction of the parent to get converted to metabolite [and preferably do simultaneous parent/metabolite modeling] c) If you have no idea about the Vm or fm then use a sequential empirical (transit/delay) compartmental modeling recently described by

Don Mager in a DMD paper [2004 Aug;32(8):786-93]
Is there any consensus on which of these 3 approaches to use. Best regards,
Mahesh


--
Nick Holford, Dept Pharmacology & Clinical Pharmacology
University of Auckland, 85 Park Rd, Private Bag 92019, Auckland, New Zealand
[EMAIL PROTECTED] tel:+64(9)923-6730 fax:+64(9)373-7090
http://www.fmhs.auckland.ac.nz/sms/pharmacology/holford

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