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Re: Is it possible that IIV (%CV) of final model was higher than IIV of base model?

From: Martin Bergstrand <martin.bergstrand>
Date: Mon, 8 Jul 2019 11:16:07 -0400

Dear Pete,

The most natural explanation for this finding is if the covariates in
question are time varying and vary rather substantially within an
individual over time. Given the listed covariates this seems likely (please
confirm if that is so). This would explain why you primarily improve
residual unexplained variability (RUV) and not IIV with the inclusion of
the covariate effects). The base model (without inter-occasion-variability
(IOV)) can’t explain time varying changes in the parameters (CL/F a=
nd V/F)
and hence true changes in parameter estimates over time results in an
inflated RUV estimate.

If the time varying covariates shows significant trends i.e. general
increase/decrease over time, the inclusion of these covariates effects can
correct a model misspecification in the base model. Under these
circumstances it likely that IIV is underestimated with the misspecified
base model and hence the apparent increase in IIV with the covariates

Depending on how sparse your observed plasma concentration measurement are
it may be a good idea to try to first characterize IOV for one or more
parameters to better understand how much of the parameter variability that
is explained by the covariates.

Kind regards,

Martin Bergstrand, Ph.D.

Principal Consultant

Pharmetheus AB

+46(0)709 994 396 <+46709%C2%A0994%20396>


+46(0)18 513 328 <+4618%20513%20328>

U-A Science Park, Dag Hammarskjölds v. 36b

752 37 Uppsala, Sweden

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On 8 Jul 2019, at 16:21, Vichapat Tharanon <vichapat.t

Dear All,

            I am a hospital pharmacist and I am working on NONMEM as a new
user. I have modeled the oral immediate-released tacrolimus (Prograf) in
adult liver transplant patients.

Most of the data were trough concentration (about 1170 levels) from routine
monitoring tacrolimus data in the period of first day post-transplantation
to 6 months. The model was constructed by NONMEM 7.2 using FOCE INTERACTION
methods with the subroutines ADVAN2 TRANS2 (one compartment model with
linear absorption and elimination). The ka could not be estimated and then
was fixed at 4.48 h-1. The IIIV and RUV were described by exponential and
additive error model, respectively. Forward addition of a liver enzyme (AL=
), Hemoglobin and total bilirubin (TB) on CL/F reduced OFV significantly (d=
OFV ~98, 42, 28, respectively) but IIV of CL/F was increased from 37.2% to
38.1%. It was found that no significant covariates influenced to V/F but
IIV of V/F was also increased from 55% to 63%. Residual variability was
reduced from a SD of 2.80 to 2.65, when compared final model and base model=

            I feel uncomfortable with these findings. Is it possible that
IIV of CL/F and V/F were rising after adding the significant covariates
whereas %RSE of the CL/F and V/F estimate as well as IIV of CL/F and IIV of
V/F in final model were slightly decreasing. May I have your comment or
suggestion; I would really appreciate it. Thank you in advance.

Best regards,


Received on Mon Jul 08 2019 - 11:16:07 EDT

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