Re: [EXTERNAL] Re: MU referencing and time-varying covariates
Thank you for the clarification. Much appreciated.
Regeneron - Internal
Quoted reply history
________________________________
From: Bauer, Robert <[email protected]>
Sent: Saturday, January 11, 2025 2:31 AM
To: 'Leonid Gibiansky' <[email protected]>; Sébastien Bihorel
<[email protected]>; [email protected]
<[email protected]>
Subject: RE: [EXTERNAL] Re: [NMusers] MU referencing and time-varying covariates
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
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
[email protected]<mailto:[email protected]>
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-----Original Message-----
From: [email protected]<mailto:[email protected]>
<[email protected]> On Behalf Of Leonid Gibiansky
Sent: Friday, January 10, 2025 5:21 PM
To: Sébastien Bihorel <[email protected]>;
[email protected]<mailto:[email protected]>
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
> [email protected]<mailto:[email protected]>
>
>
> Regeneron - Internal
>
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