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RE: algorithm limits

From: Mark Sale - Next Level Solutions <mark>
Date: Mon, 21 Jul 2008 03:01:46 -0700
<= td style="text-align: left;" align="left" valign="top" width="108">= Thanks Leonid,
 = I believe what you tell me, and I understand that FOCE doesn't solve the p= roblem with the approximation that FO makes, only reduces it (and possibly = expands the range that the approximation is useful for?).  Anyone out = there with insight into what a practical limit is for FOCE and/or if there = are any diagnostics that are helpful when you're close to it?  Is it r= eally 0.5 for FO?

Mark Sale MD
Next Level Solutions, = LLC
919-846-91= 85

-------- Original Message --------Subject: Re: [NMusers] algorithm limits
From: Leonid Gibiansky <LGib= iansky ale - Next Level Solutions <mark k="return true;Popup.composeWindow('pcompose.php?sendto=nmusers%40globo=');; return false;" href="mailto:nmusers ="_blank">
e-mail: LGibiansky at
tel: (301) 767 5566

Mark Sale - Next Level Solutions wrote:
> Leon= id,
> This isn't PK, and the model show basically the right shape, an= d the
> data suggest reasonable residual error (the biological marke= r falls from
> a value between 5 and 310000, to somewhere between 0 = and no change from
> baseline, over a course of a couple of hours to= a couple of weeks, then
> recovers somewhere between a 100 hours an= d 9000 hours later.)
> ie., it start at a highly variable level fall = by some highly variable
> fraction, over some variable lenghth of ti= me and recovers somewhere
> between about a week and about a year.> But, within those limits, it appears pretty well behaved.
> >
> Mark Sale MD
> Next Level Solutions, LLC
> <>
> 919-846-9185
> -------- Original Message ----= ----
> Subject: Re: [NMusers] algorithm limits
> From: Leonid G= ibiansky <LGibiansky com>
> Date: Sat, July 19, 2008 5:36 pm
> To: Mark Sale = - Next Level Solutions <mark>
> Cc: nmusers<= /b> pcompose.php#Compose" target="_blank" _onclick="return true;Popup.compo= seWindow('pcompose.php?'); return false;" = mce_href="">nmusers<= /b> u really have 10,000 fold differences in, say, volume or
> bioavailab= ility, population model does not make any sense: individual
> paramet= ers have uninformative priors; they are defined by the
> individual> data only, no meaningful predictions can be made for the next patien= t.
> So, if you need data description, you can directly see whether t= he
> method provides you with the correct line, but you cannot count = on
> prediction: they can be anywhere.
> For the estim= ation procedure, my understanding is that large OMEGAs
> will
>= discount population model influence on the individual fit, and in this
= > respect, the method will give you the correct answer (individual
&g= t; parameters controlled by the individual data only). This is how you
&= gt; trick nonmem into the individual model fit: assign huge OMEGAs. Whether=
> your true OMEGA value is 50 or 150 is more or less irrelevant: bot= h
> values are huge and do not provide informative priors for the
= > individual
> parameters.
> Sometimes you get huge= OMEGAs if there is a strong correlation between
> parameters, so tha= t combination of ETAs is finite while each of them
> individually can= be anywhere. Removal of some random effects can
> help in
> th= is case. Sometimes large OMEGAs are indicative of multivariate
> dist= ributions (or strong categorical covariate effects): this will be
> s= een on ETA distributions histograms or ETAs vs covariates plots.
> > Overall, I think you have problems with the model or data rather tha= n
> with the estimation method failure.
> Thanks
&g= t; Leonid
> --------------------------------------
> L= eonid Gibiansky, Ph.D.
> President, QuantPharm LLC
> web: <>
> e-mail: LGibians= ky at <>
>= ; tel: (301) 767 5566
> Mark Sale= - Next Level Solutions wrote:
> >
> > General question:<= br>> > What are practical limits on the magnitude of OMEGA that is> compatible
> > with the FO and FOCE/I method? I seem to reca= ll Stuart at one time
> > suggesting that a CV of 0.5 (exponential= OMEGA of 0.5) was about the
> > limit at which the Taylor expansi= on can be considered a reasonable
> > approximation of the real di= stribution. What about FOCE-I?
> > I'm asking because I have a mod= el that has an OMEGA of 13,
> exponential
> > (and sometime = 100) FOCE-I, and it seems to be very poorly behaved in
> > spite o= f overall, reasoable looking data (i.e., the structural model
> > = traces a line that looks like the data, but some people are WAY
> abo= ve
> > the line and some are WAY below, and some rise MUCH faster,= and some
> > rise MUCH later, by way I mean >10,000 fold, but = residual error
> looks
> > not too bad). Looking at the raw = data, I believe that the the
> > variability is at least this larg= e. Can I beleive that NONMEM FOCE
> > (FO?) will behave reasonably= ?
> > thanks
> > Mark
> >
  Thanks for your views on this - are there some simulatio= n results that you've seen, or other basis for the limit of 2-3? 

Mark Sale MD
Next Level Solutions, LLC

-------- Original Message --------
Subject: Re: [NMusers] algorithm limits
From: saik.urien.svp < To: Mark Sale - Next Level Solutions <mark Cc: Mark, Leonid
I suspe= ct that OMEGA values above 2 or 3 units are very doubtful. As Leonid p= ointed out, such variability levels does not tell us anything on priors. An= other point to discuss about is the s.e. that are associated to these OMEGA= estimates. What is their extent ?
Finally= with such results I would have subjected the model to a bootstrap evaluati= on , to check the true confidence intervals of the model estimates.<= /div>
Saïk<= /font>
<= div style="font-family: arial; font-style: normal; font-variant: normal; = font-weight: normal; font-size: 10pt; line-height: normal; font-size-adjust= : none; font-stretch: normal;">----- Original Message -----
Subject: RE: [NMusers] algorithm limits

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Received on Mon Jul 21 2008 - 06:01:46 EDT

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