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Coding delayed covariate effects

From: Elisabet Størset <elisabet.storset>
Date: Thu, 23 Feb 2012 20:50:56 +0100

Dear nonmemusers

In my PK modeling project, a drug (elimination: 100 % hepatic metabolism)
is given orally twice daily over a period of 10 weeks. 100 subjects
contribute daily trough concentrations. During this period, covariates vary
within subjects. Two covariates that are difficult to handle are changes in
corticosteroid regime and changes in cytokine concentrations, which both
are expected to alter metabolism (CYP enzymes) at a transcriptional level.
This means that a covariate effect on CL is expected to be delayed and/or
last for some time (unknown for how long).

My first strategy is to code this in the normal way:

TVCL=THETA(1) + THETA(2) *(cytokine concentration) or (corticosteroid dose)

However, when coding the covariate as continuous with this method, it will
not take into account that an effect does still have an impact on the
parameter after the covariate value has returned to normal in the data set.

Example 1 - Low dose steroids are typically administered daily. Then, high
dose methylprednisolone is given I.V. for 3 days, before going back to the
low dose. The inductive effect on CYP enzymes from the high dose could be
delayed and then last for 1-2 weeks even though the high dose is not

Example 2 - Cytokines marks an inflammation, which could have temporary
impact on CL/F. Cytokine concentration returns to normal, but the impact on
the parameter could be lasting for some days.

Does anyone have experience of a strategy to code these kinds of covariate
relationships in NONMEM? Could NONMEM estimate for how long time CL/F might
be affected, or is this too much to ask for? :)

Additional question: Is there any way to make the visual predictive check
an appropriate validation method when only trough concentrations are known
over a long period of time, when doses are frequently changing within and
between subjects during the period?

Thank you all in advance for your kind help :)

Elisabet, pharmacy student, University of Bergen

Received on Thu Feb 23 2012 - 14:50:56 EST

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