NONMEM Users Network Archive

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Re: Questions about identifiability

From: Amy Cheung <sya.cheung>
Date: Fri, 13 Apr 2007 13:55:58 +0100

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 t=
o 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 r=
eal 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-compar=
tment
> > model with non–linear protein binding in the central and in the perip=
heral
> > compartment, which from a physiological point of view makes complete se=
nse.
> > 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 N=
ONMEM
> > 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 ident=
ical
> > to the original ones, %SE is very small) we concluded that the stru=
cture
> > in principle is identifiable.
> >
> >
> >
> > · Our second question was: "Are the time points of the given st=
udy
> > 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 estim=
ates
> > were again nearly identical to the original ones and %SE is still v=
ery
> > small (below 0.3 %).
> >
> > · Our third question was: "Could the parameters still be re-est=
imated
> > if we assume inter- and intra-subject variability for the simulation st=
ep?"
> >
> > We simulated the given dataset assuming IIV, IOV and residual e=
rror.
> > Under these conditions, the parameter (fixed and random effect) esti=
mates
> > are again similar, but not identical to the original ones, %SE increase=
d to
> > about 9% (one exception is the SE% of the parameter for the amoun=
t 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 diff=
icult
> > 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 t=
he
> > structure of the model remain stable?
> >
> > 3. How often would you simulate and re-estimate the third experime=
nt?
> > 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 qui=
te
> > 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 - 08:55:58 EDT

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