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Re: estimating Ka from dataset combining rich sample study and sparse sampling study

From: Ethan Wu <ethan.wu75>
Date: Wed, 17 Jun 2009 12:43:14 -0700 (PDT)

Dear Juergen,   thanks for your comment.   I was actually=
 not aware such full non-parametric approach, apology for my ignorance. the=
 approach is very intersting, I will try to understand it more. =
  with regards to non-parametric approach, I was thinking al=
one the line of estimation method for Eta only as offered in nonmem. =

 Eta for Ka still estimated to be very small, 5.50E-08 vs 0.13 estimated by=
 using rich data only.   ____________________________=
____ From: Jurgen Bulitta <jbulitta
>; Roger Jelliffe <jelliffe
ent: Wednesday, June 17, 2009 2:42:31 PM Subject: RE: [NMusers] estimatin=
g Ka from dataset combining rich sample study and sparse sampling study =

 of moving forward. I have no personal experience with the hybrid method.=

k better and is mathematically more consistent. This approach should not=
 suffer from shrinkage.   I would expect this algorithm to behave =
as follows: 1) The subjects with rich data should be essentially complete=
ly unaffected by the subjects with sparse data. 2) The subjects with s=
parse data should have posterior (i.e. intra-individual) probability dist=
ributions of Ka which are similar to the inter-individual distribution of=
 Ka for the population of subjects with rich data.   Depending on =
how the distribution of individual Ka values of the subjects with rich da=
ta look, you may or may not get a multimodal intra-individual distributi=
on of Ka for the patients with sparse data. This may become important for=
 the covariate relationships which you are trying to develop subsequently=
..   Please let me know, if Roger’s group or I can be of he=
lp to set you up, if you want to use NPAG for solving this task.  =

com [mailto:owner-nmusers
nesday, June 17, 2009 11:21 AM To: nmusers
sers] estimating Ka from dataset combining rich sample study and sparse sam=
pling study   Dear all,   I am working on this pop PK analy=
sis. the objective is, to explore some covariates on the exp=
osure.   the dataset has rich sampled study, with absorption ph=
ase well captured. and also sparse sampling study with only trough sample, =
and another sample around 1-2hr after dosing  with rich sample study=
 data, the ka and eta on Ka is well estimated using FOCE INT method and 1ct=
 1st order model.  but when with pooled dataset, using the same=
 model and method, eta on Ka is estimated to be almost 0, the fit to t=
he data from rich sampled study became little worse on the peak.   I=
s there way to keep a good estimation of Eta on Ka, which is to make s=
ure the good capture of Cmax, at least for rich sampled subjects?  =

n ka with the estimate from rich sample study alone  -- hybrid estim=
ating methods  -- nonparametric method    Any comment=
s will be highly appreciated.
Received on Wed Jun 17 2009 - 15:43:14 EDT

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