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

From: Jurgen Bulitta <jbulitta>
Date: Wed, 17 Jun 2009 14:42:31 -0400

Dear Ethan,

Your first suggestion would be a pragmatic way of moving forward.
I have no personal experience with the hybrid method.
Your third suggestion, using a full non-parametric approach
should work 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 completely
unaffected by the subjects with sparse data.
2) The subjects with sparse data should have posterior (i.e. intra-individu=
al)
probability distributions 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 data look, you may or may not get a
multimodal intra-individual distribution 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 help to set
you up, if you want to use NPAG for solving this task.

Best wishes
Juergen

From: owner-nmusers
Behalf Of Ethan Wu
Sent: Wednesday, June 17, 2009 11:21 AM
To: nmusers
Subject: [NMusers] estimating Ka from dataset combining rich sample study a=
nd sparse sampling study

Dear all,
I am working on this pop PK analysis. the objective is, to explore some c=
ovariates on the exposure.
the dataset has rich sampled study, with absorption phase 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 i=
s estimated to be almost 0, the fit to the data from rich sampled study bec=
ame little worse on the peak.
Is there way to keep a good estimation of Eta on Ka, which is to make sur=
e the good capture of Cmax, at least for rich sampled subjects?

with my limited knowledge, I was thinking:
-- fixing Eta on ka with the estimate from rich sample study alone
-- hybrid estimating methods
-- nonparametric method

Any comments will be highly appreciated.

Received on Wed Jun 17 2009 - 14:42:31 EDT

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