Re: time-dependent residual error models
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 Theta’s, Eta’s, and Epsilon’s
LTH gives the maximum number of theta’s allowable. It must be between 1 and 70. LVR gives the maximum number of eta’s plus epsilon’s 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.
>
Quoted reply history
> -----Original Message-----
> From: [email protected] [mailto:[email protected]]
> 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: [email protected]
>
> [mailto:[email protected]]
>
> > 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: [email protected]
> >
> > [mailto:[email protected]] On
> >
> > > 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
[email protected] tel:+64(9)923-6730 fax:+64(9)373-7090
mobile: +64 21 46 23 53
http://www.fmhs.auckland.ac.nz/sms/pharmacology/holford