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Re: time-dependent residual error models

From: Nick Holford <n.holford>
Date: Sat, 03 Oct 2009 08:52:53 +1300

Phylinda,

Thanks for the explanation about the impracticability of using the
'complex flexible input' model. However, I would have thought the
problem was not the run time but the upper limit on number of THETAs of
70 and on OMEGA+SIGMA of 70 in NONMEM (still there in NONMEM 7!).

"/III.2.9.1. Changing the Number of Thetaís, Etaís, and Epsilonís
LTH gives the maximum number of thetaís allowable. It must be between 1
and 70.
LVR gives the maximum number of etaís plus epsilonís allowable. It must
be between 1 and 70/" NONMEM VI User Guide III

Where would you get the ultra-big NONMEM version with 97 THETAs and 87
OMEGAs?

Nick

Chan, Phylinda wrote:
> Hi Nick,
>
> There are 97 thetas and 87 omegas in the complex flexible input model.
> Despite of the run time, it is impractical to apply such model for
> covariates searching in the meta-analysis.
>
> Phylinda.
>
>
> -----Original Message-----
> From: owner-nmusers
> On Behalf Of Nick Holford
> Sent: 30 September 2009 04:31
> To: nmusers
> Subject: Re: [NMusers] time-dependent residual error models
>
> 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
>>
> [mailto: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 Fri Oct 02 2009 - 15:52:53 EDT

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