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Re: time-dependent residual error models

From: Nick Holford <n.holford>
Date: Wed, 30 Sep 2009 16:30:47 +1300

Phylinda,

Thanks for the explanation -- it seems that the more usual approach of
complex structure+simple residual error model had already been done by
Barry Weatherley.
Your simple structure+complex residual error is an interesting
alternative but apart from your feelings ("We felt ...") was there any
reason not to use Barry's structural model?

Nick

Chan, Phylinda wrote:
> Hi Nick,
>
> Being a substrate of P-gp and CYP3A4, the compound itself has a very
> complex absorption profile including dose non-linearity, double peaks,
> food effects as well as high between individual and within individual
> variability. Barry Weatherley has spent a substantial amount of time
> and effort in understanding the dose non-linearity and some covariate
> effects on the PK of this compound, including development of a very
> complex flexible input model which was presented at PKUK in 2004. More
> details of some of this modelling work can be found in a recent
> publication.
>
> http://www3.interscience.wiley.com/journal/122386172/abstract
>
>
> The main objective of the meta-analysis was to develop a compartmental
> model which would be useful in identifying significant covariates
> explaining inter-individual variability and was simple enough to be used
> in the later modelling of sparsely sampled PK in phase 2b/3 studies
> where a full time profile and samples were likely to be clustered in the
> elimination phase of the PK. We felt the first-order input with dose
> and food effects on Ka in addition to the time-dependent residual error
> model was adequate for this purpose.
>
>
> For those who interested in the coding of the time-dependent residual
> error model:
> $ERROR
> IPRED = F+.00001
> LPRED = 0
> IF(IPRED.GT.0) LPRED = LOG(IPRED)
>
> PMAX=THETA(7)
> TMAX=THETA(8)
> K=THETA(9)
> BASE=THETA(10)
>
> P=K*TMAX
> A=EXP(P)/TMAX**P
>
> W= PMAX*A*(TAD+.01)**P*EXP(-K*(TAD+.01))+BASE
> IRES= DV-LPRED
> IWRES= IRES/W
> Y= LPRED+EPS(1) * W
>
> Note:
> i) $SIGMA (1 FIX)
> ii) TAD=time after dose
>
> Phylinda.
>
>
> -----Original Message-----
> From: owner-nmusers
> On Behalf Of Nick Holford
> Sent: 24 September 2009 08:42
> To: nmusers
> Subject: Re: [NMusers] time-dependent residual error models
>
> Mats,
>
> I agree with your general idea but in this particular case there is no
> description in the paper of efforts made to test structural models for
> absorption apart from first order input with dose and food effects on
> Ka. There seems to be quite a lot of time related structure in the
> residual error model function that Phylinda reported and I would have
> thought that at least some of this could have been explored via another
> structural model e.g. involving parallel or sequential zero-order
> inputs. It struck me as a rather unusual approach and I wondered what
> the reasons for it were.
>
> It does not really bother me which approach is used when describing
> absorption (fancy structure+vanilla residual or vanilla structure+fancy
> residual) because the details of the rate of absorption rarely have any
> clinical relevance (Justin Wilkins may want to disagree <grin>). Of
> course, as you point out the errors may often arise from poorly
> reproducible fixed effects such as timing errors etc. and thus the goal
> may be to describe the error adequately and not the structure because
> the structure is not really fixed or of any interest.
>
> Nick
>
>
> Mats Karlsson wrote:
>
>> Hi Nick,
>>
>> I can't answer for Phylinda, but the general idea is to build the most
>> appropriate structural model that is supported by data. However, after
>>
> that
>
>> is done, if there still is variation in residual error magnitude one
>>
> should
>
>> take that into account and not ignore it. All models are wrong, and I
>>
> would
>
>> say that in general our models for absorption are more wrong than our
>>
> models
>
>> for disposition. That is not just because we have focused more on the
>> latter, but because the underlying processes governing absorption are
>>
> of a
>
>> different nature (e.g. with discrete events like food intake, gastric
>> emptying, bile release and formulation disintegration and movement).
>>
> Further
>
>> often part of the error magnitude is from timing errors. Such errors
>>
> are
>
>> more pronounced when concentrations are changing fast (normally
>>
> fastest
>
>> changes in absorption phase). We wrote on time-varying residual errors
>>
> (and
>
>> alternatives such as residual error magnitude related to rate of
>>
> change) in
>
>> these publications:
>> J Pharmacokinet Biopharm. 1995 Dec;23(6):651-72.
>> J Pharmacokinet Biopharm. 1998 Apr;26(2):207-46
>>
>> Best regards,
>> Mats
>>
>> Mats Karlsson, PhD
>> Professor of Pharmacometrics
>> Dept of Pharmaceutical Biosciences
>> Uppsala University
>> Box 591
>> 751 24 Uppsala Sweden
>> phone: +46 18 4714105
>> fax: +46 18 471 4003
>>
>>
>> -----Original Message-----
>> From: owner-nmusers
>>
> [mailto:owner-nmusers
>
>> Behalf Of Nick Holford
>> Sent: Thursday, September 24, 2009 7:46 AM
>> To: nmusers
>> Subject: Re: [NMusers] time-dependent residual error models
>>
>> Hi,
>>
>> If Phylinda reads this I'd be interested to hear why she choose to use
>>
> a
>
>> plain vanilla first-order absorption model and a fancy time-dependent
>> residual error model rather than trying to model a fancy absorption
>> process with a plain vanilla residual error model?
>>
>> Nick
>>
>> Joseph Standing wrote:
>>
>>
>>> Xiang,
>>>
>>>
>>>
>>> There is a rather elegant time-dependent residual error model
>>> described by Phylinda Chan et al in:
>>>
>>> BJCP, 2008;65(S1):76-85.
>>>
>>>
>>>
>>> BW,
>>>
>>> Joe
>>>
>>>
>>>
>>
>>
>
>

--
Nick Holford, Professor Clinical Pharmacology
Dept Pharmacology & Clinical Pharmacology
University of Auckland, 85 Park Rd, Private Bag 92019, Auckland, New Zealand
n.holford
mobile: +64 21 46 23 53
http://www.fmhs.auckland.ac.nz/sms/pharmacology/holford
Received on Tue Sep 29 2009 - 23:30:47 EDT

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