- On 12 Oct 2005 at 14:24:43, "Jing Li" (jli29.-a-.jhmi.edu) sent the message

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Hi,

I am running a 3-compartmental PK model with a non-linear elimation

(Michealis-Menten) from the central compartment. The data were from

3 trials with total patients of 224. The drug was given as 20-min iv

infusion weekly or every three weeks at different dose leves.

When it was run with first order (FO) estimation, the model got

converged successfully and produced very reasonable PK parameters

(THETAs), inter-individual variabilities (ETAs), and relative

standard errors of estimations. The fitting looks pretty good.

However, when it runs with first order conditional estimation (FOCE),

convergence becomes almost impossible. Interation becomes extremely

slow, and after several iterations, there is always an error message

like "...Occurs during search for ETA at a nonzero value of ETA.

Numerical difficulties with integration routine. Maximum No. of

evaluaitons of differential equations exceeded 100000".

Does anyone have some good ideas to solve this problem? I appreciate!

Also, is it acceptable to report parameters produced by FO? I am

wondering if there are some guidelines or references for the choice

of FO and FOCE.

Thanks you in advance for any help!

Sincerely,

Jing - On 12 Oct 2005 at 18:02:14, "Bhattaram, Atul" (BhattaramA.aaa.cder.fda.gov) sent the message

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The following message was posted to: PharmPK

Hello Jing

The difficulties with FOCE can often be resolved with a simpler

structure

for your random effects in your model. It is a common issue that is

observed

as you (error message)use methods that are more complex such as FOCE or

FOCE+Interaction in comparison to FO. Results from FO method are often

published in literature. It also depends on the purpose of your

modeling of

the data. If the analysis would result in critical recommendations

then it

might be useful to run your models with methods such as FOCE etc.

Venkatesh Atul Bhattaram

Pharmacometrics

DPE-1, OCPB

CDER, FDA. - On 13 Oct 2005 at 09:06:17, "Bonate, Peter" (Peter.Bonate.at.genzyme.com) sent the message

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The following message was posted to: PharmPK

Jing,

What you are seeing is a fairly common experience. You can try a

number of

different things, none of which will really speed up the run times.

They are

what they are. First, try using a transform-both-sides approach

using the

Ln-transformation. Modeling on a log-scale always seems to help.

Second,

you might try reparameterizing your Michaelis-menten model to a more

stable

form. There are two possibilities here:

Cp = A(1)/V1

CL = Vmax/(exp(km) + Cp)

or

Cp = A(1)/V1

CL = CL_linear/(1 + alpha*Cp)

You can also reduce the number of variance components, especially

near zero

ones.

I wish I had a solution to the Maxevals problem short of changing the

NONMEM

code.

Good luck,

Pete Bonate

Peter L. Bonate, PhD, FCP

Director, Pharmacokinetics

Genzyme Corporation

4545 Horizon Hill Blvd

San Antonio, TX 78229

phone: 210-949-8662

fax: 210-949-8219

email: peter.bonate.-a-.genzyme.com - On 13 Oct 2005 at 15:49:30, "Elassaiss - Schaap, J. (Jeroen)" (jeroen.elassaiss.-at-.organon.com) sent the message

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The following message was posted to: PharmPK

Dear Jing,

You may want to browse the nmusers list archives for more tips, but the

solution to your problem is described in

http://huxley.phor.com/nonmem/nm/98oct071998.html

For guidelines regarding the use of conditional estimation methods,

see the conditional estimations guide (part VII of the nonmem users

guide).

Best regards,

Jeroen

J. Elassaiss-Schaap

Scientist PK/PD

Organon NV

PO Box 20, 5340 BH Oss, Netherlands

Phone: + 31 412 66 9320

Fax: + 31 412 66 2506

e-mail: jeroen.elassaiss.aaa.organon.com

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