# RE: NONMEM message

From: Ken Kowalski <ken.kowalski>
Date: Thu, 13 Nov 2008 10:35:30 -0500

Mitsuo,

This is a new message specific to NONMEM VI. I must confess I don't know
what to make of this message myself. It would be informative if someone
could tell us what internals in NONMEM trigger this message (i.e., "PROBLEMS
OCCURRED WITH THE MINIMIZATION").

With respect to your two model runs note that they are really two different
parameterizations. In the first parameterization, where

TVCL = THETA(1) * THETA(2) ** SEX

note that THETA(1) represents the true value of CL for males and THETA(2)
represents the ratio of CL between females to males. In the second
parameterization, where

TVCL = THETA(1)
IF (SEX.EQ.1) TVCL = THETA(2)

note that THETA(1) and THETA(2) represent the true values of CL for males
and females, respectively. Thus, THETA(2) has a different interpretation
between these two parameterizations.

A third parameterization that you could consider is

TVCL = THETA(1) *(1 + THETA(2))**SEX or equivalently, TVCL = THETA(1) * (1 +
THETA(2)*SEX)

where THETA(1) is again the true value of CL for males and THETA(2) is the
fractional change in CL for females relative to males.

Each of these parameterizations should result in the same model fit (i.e.,
minimum value of the OFV) but one parameterization may be more stable than
another...it is similar to the issue with continuous covariates where we
center or scale the covariate based on the mean or median value (i.e.,
centering or scaling will reduce the correlation in the estimates between
the intercept term and the covariate effect which should lead to a more
stable model and faster convergence to the minimum OFV).

I would look at the COV step output and in particular, look at the
correlation of the estimates between THETA(1) and THETA(2) for these
different parameterizations. My guess is that the correlation is higher for
the first parameterization (given that you indicate that it gives this
warning message and that the second parameterization does not). You can
also use the PRINT=E option on the COV statement and look at the ratio of
the largest to the smallest eigenvalues to more globally assess the
stability of your model. In the end, if they all converge to the same final
OFV and if you really want to estimate the ratio of CLs between males and
females then so be it even if the model is less stable and NONMEM gives you
this warning message. On the other hand, if the different parameterizations
don't converge to the same OFV then you need to look more closely at how you
parameterize the covariate effect. If you get a lower OFV with the second
parameterization because it is more stable and NONMEM has an easier time
iterating to the minimum OFV then I would go with that parameterization and
if you want to estimate the ratio of the CLs you can always estimate it as
THETA(2)/THETA(1) (i.e., which is equivalent to THETA(2) in the first
parameterization.

I hope this helps.

Ken

Kenneth G. Kowalski
President & CEO
A2PG - Ann Arbor Pharmacometrics Group, Inc.
110 E. Miller Ave., Garden Suite
Ann Arbor, MI 48104
Work: 734-274-8255
Cell: 248-207-5082
Fax: 734-913-0230
ken.kowalski

-----Original Message-----
From: owner-nmusers
Behalf Of Higashimori, Mitsuo
Sent: Wednesday, November 12, 2008 10:06 PM
To: nmusers
Subject: [NMusers] NONMEM message

Dear all,

I have a following error(?) massage on a poplation analysis using NONMEM VI.

0MINIMIZATION SUCCESSFUL
HOWEVER, PROBLEMS OCCURRED WITH THE MINIMIZATION.
REGARD THE RESULTS OF THE ESTIMATION STEP CAREFULLY, AND ACCEPT THEM ONLY
AFTER CHECKING THAT THE COVARIANCE STEP PRODUCES REASONABLE OUTPUT.

I found it when I described a control stream to assess sex difference on
oral clearance as shown in below,

TVCL = THETA(1) * THETA(2) ** SEX
where SEX=0 for male and SEX=1 for female.

This message was displayed without any error message. It was not
dissapeared even though I changed the initial parameters. However, it was
solved when I changed the model definition. For example,

TVCL = THETA(1)
IF (SEX.EQ.1) TVCL = THETA(2)

Could you please let me know some details regarding the message.
Especially, I'd like to know

1. What impact does this error message give the analysis result?
2. Why does it depend on the model definition?

Thanks,

_/ _/ _/ Mitsuo Higashimori, Ph.D.
_/ _/ _/ Pharmacokinetic Group, Early Phase Development Department
_/ _/ _/ Clinical Division, Research & Development
_/ _/ _/ AstraZeneca K.K.
_/ _/ _/ E-mail: Mitsuo.Higashimori

Received on Thu Nov 13 2008 - 10:35:30 EST

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