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RE: Questions about identifiability

From: Xiao, Alan <Alan.Xiao>
Date: Fri, 13 Apr 2007 23:41:26 -0400

sorry that I followed with the wrong email.

Alan

-----Original Message-----
From: sya.cheung
Cheung
Sent: Friday, April 13, 2007 8:56 AM
To: Xiao, Alan
Cc: nmusers
Subject: Re: [NMusers] Questions about identifiability


Dear Alan,

The problem was originally posted by Silke Dittberner. I am just
helping in solving the problem and my email was to express interest to
the nature of the model in order to answer the structural
identifiability problem. I think you should email your comment
addressed to Silke Dittberner at
Silke.Dittberner

Many thanks,

Amy



On 13/04/07, Xiao, Alan <Alan.Xiao
> Amy,
>
> Just one comment about identifiability. A very simple and efficient =
way to see whether your model has identifiability problem is to randomly =
change your initial guesses to see whether your parameter estimates are =
stable. In addition, that your simulation proves no identifiability =
problem does not necessarily mean your model will not have =
identifiability problem to your real data.
>
> Alan
>
> -----Original Message-----
> From: owner-nmusers
> [mailto:owner-nmusers
> Sent: Friday, April 13, 2007 4:45 AM
> To: Silke.Dittberner
> Cc: nmusers
> Subject: Re: [NMusers] Questions about identifiability
>
>
> Dear Silke,
>
> Before looking into the identifiability question, it is useful to know
> what the differential equations and the dosing route are, please?
>
> Kind regards,
>
> Amy
>
> =
-------------------------------------------------------------------------=
------
> S.Y.A. Cheung
> Postgraduate Research Student
> The Centre for Applied Pharmacokinetic Research (CAPKR)
> School of Pharmacy and Pharmaceutical Sciences
> University of Manchester
> Stopford Building
> Oxford Road
> Manchester
> U.K.
>
> =
-------------------------------------------------------------------------=
----------------------------------------------
>
> On 13/04/07, Silke.Dittberner
> <Silke.Dittberner
> >
> >
> > Dear NONMEM users,
> >
> > The PK of the compound we are working on can be described by a =
2-compartment
> > model with non–linear protein binding in the central and in the =
peripheral
> > compartment, which from a physiological point of view makes complete =
sense.
> > The question we have is whether such model is identifiable having =
just total
> > plasma concentration (no binding information is available).
> >
> > Therefore we want to simulate different kind of datasets and check =
if NONMEM
> > is able to re-estimate them properly.
> >
> >
> > · Our first question was: "Is the structure itself in =
principle
> > identifiable?"
> >
> > We simulated a dataset with 100 time points per subject and =
no
> > intra- or inter-individual variability and no residual error. =
('ideal' data:
> > plenty time points, no random error) Since under these =
conditions the
> > parameters could be re-estimated (parameter estimates were nearly =
identical
> > to the original ones, %SE is very small) we concluded that the =
structure
> > in principle is identifiable.
> >
> >
> >
> > · Our second question was: "Are the time points of the given =
study
> > sufficient to estimate all parameters assuming 'ideal' data?"
> >
> > We simulated the given dataset assuming no intra- or
> > inter-individual variability and no residual error. The parameter =
estimates
> > were again nearly identical to the original ones and %SE is =
still very
> > small (below 0.3 %).
> >
> > · Our third question was: "Could the parameters still be =
re-estimated
> > if we assume inter- and intra-subject variability for the simulation =
step?"
> >
> > We simulated the given dataset assuming IIV, IOV and =
residual error.
> > Under these conditions, the parameter (fixed and random effect) =
estimates
> > are again similar, but not identical to the original ones, %SE =
increased to
> > about 9% (one exception is the SE% of the parameter for the =
amount of
> > peripheral binding sites which were estimated to be 16%). However, =
when we
> > re-estimate omitting the IIV and IOV, the estimated parameters =
differ from
> > the original ones and estimates for the peripheral binding becomes =
difficult
> > to estimate.
> >
> > The questions we have are:
> > 1. Are these experiments sufficient to conclude on the model
> > identifiability?
> > 2. Does it make sense that the fixed effect parameters differ =
from the
> > original ones when IIV and IOV are omitted in the estimation step in
> > constrast to when they are included in the simulation step? =
Shouldn't the
> > structure of the model remain stable?
> >
> > 3. How often would you simulate and re-estimate the third =
experiment?
> > 4. Would you vary the initial estimates to check for any =
potential
> > other set of parameters? (If yes how often?)
> > 5. One problem is that the complete model with IIV and IOV has =
quite
> > long run times (around 24h), do you think checking the model with =
just IIV
> > would be enough?
> >
> > 6. Do you have any other proposal to check for the =
identifiability of a
> > model?
> >
> > Your help is highly appreciated, thank you in advance,
> >
> > Silke
> >
> >
> >
> > Silke Dittberner
> > PhD student
> > Institute of Pharmacy
> > University Bonn
> > Germany
>
>
> --
>


--
-------------------------------------------------------------------------=
------
S.Y.A. Cheung
Postgraduate Research Student
The Centre for Applied Pharmacokinetic Research (CAPKR)
School of Pharmacy and Pharmaceutical Sciences
University of Manchester
Stopford Building
Oxford Road
Manchester
U.K.



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Received on Fri Apr 13 2007 - 23:41:26 EDT

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