RE: Questions about identifiability

-----Original Message----- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] Behalf Of Amy Cheung Sent: Friday, April 13, 2007 8:56 AM To: Xiao, Alan Cc: [EMAIL PROTECTED] 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 [EMAIL PROTECTED] instead of me. Many thanks, Amy On 13/04/07, Xiao, Alan <[EMAIL PROTECTED]> wrote: > 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: [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 > > > -- > -- ------------------------------------------------------------------------------- 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. /\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\ "For beautiful eyes, look for the good in others; for beautiful lips, speak only words of kindness; and for poise, walk with the knowledge that you are never alone. People, even more than things, have to be restored, renewed, revived, reclaimed, and redeemed; never throw out anyone. Remember, if you ever need a helping hand, it's at the end of your arm, as you get older, remember you have another hand: The first is to help yourself, the second is to help others." Audrey hepburn /\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/