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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 13:41:10 -0700 (PDT)

Dear Leonid   yes, this is another way to move forward, similar as f=
ixing eta to estimate from rich data. _____________________________=
___ From: Leonid Gibiansky <LGibiansky
han.wu75
users
c.edu>; "Neely, Michael" <mneely
4:30:08 PM Subject: Re: [NMusers] estimating Ka from dataset combining ri=
ch sample study and sparse sampling study You can try IF(RICH dat=
a) THEN   KA=THETA(1)*EXP(ETA(1)) ELSE KA=THETA(1) ENDIF=

esident, QuantPharm LLC web:    www.quantpharm.com e-mail: LG=
ibiansky at quantpharm.com tel:    (301) 767 5566 =

nt. >  I was actually not aware such full non-parametric approach, a=
pology for my ignorance. the approach is very intersting, I will try to und=
erstand it more. >    with regards to non-parametric approach, =
I was thinking alone the line of estimation method for Eta only as offered =
in nonmem. >  so I went ahead tried $NONPARAMETRIC UNCONDITIONAL opt=
ion, but the 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
 *Cc:* "nmusers
elliffe
June 17, 2009 2:42:31 PM > *Subject:* RE: [NMusers] estimating Ka from da=
taset combining rich sample study and sparse sampling study > > Dear E=
than, > >  > Your first suggestion would be a pragmatic way of=
 moving forward. > > I have no personal experience with the hybrid met=
hod. > > Your third suggestion, using a full non-parametric approach=

> This approach should not suffer from shrinkage. > >  > I wou=
ld expect this algorithm to behave as follows: > > 1) The subjects wit=
h rich data should be essentially completely > > unaffected by the sub=
jects with sparse data. > > 2) The subjects with sparse data should ha=
ve posterior (i.e. intra-individual) > > probability distributions of =
Ka which are similar to the inter-individual > > distribution of Ka fo=
r the population of subjects with rich data. > >  > Depending =
on how the distribution of individual Ka values of > > the subjects wi=
th rich data look, you may or may not get a > > multimodal intra-indiv=
idual distribution of Ka for the patients > > with sparse data. This m=
ay 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 wa=
nt to use NPAG for solving this task. > >  > Best wishes > =

m.com [mailto:owner-nmusers
nt:* Wednesday, June 17, 2009 11:21 AM > *To:* nmusers
 *Subject:* [NMusers] estimating Ka from dataset combining rich sample stud=
y and sparse sampling study > >  > Dear all, > >  I =
am working on this pop PK analysis. the objective is, to explore some covar=
iates on the exposure. > >  the dataset has rich sampled study, w=
ith absorption phase well captured. and also sparse sampling study with onl=
y trough sample, and another sample around 1-2hr after dosing > >=
with rich sample study data, the ka and eta on Ka is well estimated usi=
ng FOCE INT method and 1ct 1st order model. > >  but when with po=
oled dataset, using the same model and method, eta on Ka is estimated to be=
 almost 0, the fit to the data from rich sampled study became little worse =
on the peak. > >  Is there way to keep a good estimation of Eta o=
n Ka, which is to make sure the good capture of Cmax, at least for rich sam=
pled subjects? > >  >  with my limited knowledge, I was t=
hinking: > >  -- fixing Eta on ka with the estimate from rich sam=
ple study alone > >  -- hybrid estimating methods > >  =
-- nonparametric method > >  >  Any comments will be high=
ly appreciated. > >  >  >  > =
 
Received on Wed Jun 17 2009 - 16:41:10 EDT

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