Is this also true for the FOCEI when MU-referencing is present, or only
for SAEM/IMP/etc "new" methods?
Thank you
Leonid
On 1/11/2025 2:31 AM, Bauer, Robert wrote:
If a covariate varies across records within a subject, NONMEM obtains a
simple average among the records and uses this as the covariate value
for that subject.
Robert J. Bauer, Ph.D.
Senior Director
Pharmacometrics R&D
ICON Early Phase
731 Arbor way, suite 100
Blue Bell, PA 19422
Office: (215) 616-6428
Mobile: (925) 286-0769
robert.ba...@iconplc.com <mailto:robert.ba...@iconplc.com>
www.iconplc.com <http://www.iconplc.com>
-----Original Message-----
From: owner-nmus...@globomaxnm.com <mailto:owner-nmus...@globomaxnm.com>
<owner-nmus...@globomaxnm.com> On Behalf Of Leonid Gibiansky
Sent: Friday, January 10, 2025 5:21 PM
To: Sébastien Bihorel <sebastien.biho...@regeneron.com>;
nmusers@globomaxnm.com <mailto:nmusers@globomaxnm.com>
Subject: [EXTERNAL] Re: [NMusers] MU referencing and time-varying covariates
Hi Sébastien,
As you did these experiments, can you share the results: have you seen
any differences in the fit, parameter estimates, precision, convergence
speed (number of iteration), and evaluation time for SAEM/IMP (I think,
FOCEI does not have this restriction of time-independence even if you
use Mu referencing, so results should be identical or very close).
As code is encrypted, only Bob can answer the question but my
understanding is that some kind of averaging is used to get time
independent value of WT that is then used by the SAEM/IMP algorithm for
parameter update procedure.
As WT changes slowly and not very significantly, it could be hard to see
the differences. A more stringent test would be to use time-dependent
and strongly influential ADA (0/1): how bad is the incorrect version 1
in this case?
Thank you
Leonid
On 1/10/2025 2:56 PM, Sébastien Bihorel wrote:
>
> Happy New Year,
>
> I hope everybody is ready for a great 2025 !
>
> I'll start my message/question by defining 2 different ways of coding
> a simple power relationship between body weigh on clearance.
>
> *
> Coding 1
>
> MU_1 = THETA(1) + THETA(2) * LOG(WGT/70) CL = EXP( MU_1 + ETA(1) )
>
> *
> Coding 2
>
> MU_1 = THETA(1)
> CL = EXP( MU_1 + ETA(1) ) * ( WGT/70 )**THETA(2)
>
> The reference and training materials for NONMEM clearly indicate that
> MU variables should be time invariant within occasions and recommend
> using coding 2 when body weight is time varying. Nevertheless, it is
> possible for an analyst to use coding 1. As far as I can tell from
> some limited testing, this is not a "fatal" error. Either with FOCE(I)
> or SAEM/IMP, NONMEM reports a warning but performs the model
> optimization. The table outputs also report CL as a time varying
> variable changing as body weight changes.
>
> So my questions are the following: when coding 1 is used and body
> weight is time varying, what is NONMEM actually doing during model
> optimization? Does NONMEM internally create occasions to break the
> records by interval of constant body weight and constant MU1?
> Alternatively, does NONMEM internally calculate an average of MU1?
> Something entirely different? What's the risk taken by an analyst when
> using coding 1 versus coding 2?
>
> Thank you in advance for you input
>
>
> __
> Sébastien Bihorel
> Director, Quantitative Pharmacology
> +1 914-648-9581
> sebastien.biho...@regeneron.com <mailto:sebastien.biho...@regeneron.com>
>
>
> Regeneron - Internal
>
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