RE: Questions about identifiability

-----Original Message----- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] Behalf Of Amy Cheung Sent: Friday, April 13, 2007 4:45 AM To: [EMAIL PROTECTED] Cc: [EMAIL PROTECTED] 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, [EMAIL PROTECTED] <[EMAIL PROTECTED]> wrote: > > > 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 --