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Re: Simultaneous vs sequential for modeling parent AND metabolites in pop PK

From: Nick Holford <n.holford>
Date: Thu, 11 Dec 2008 13:36:52 +1300


I agree that if you are happy with the model structure then it can be
useful to do a simultaneous fit of parent and metabolite. However, a
sequential process may be useful to evaluate the model structure


Samtani, Mahesh [PRDUS] wrote:
> 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: owner-nmusers
> [mailto:owner-nmusers
> Sent: Wednesday, December 10, 2008 3:12 PM
> To: nmusers
> 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
> 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
Received on Wed Dec 10 2008 - 19:36:52 EST

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