Dear NM-users,
We developed a PK model using NONMEM for a drug using a 2-cpt model with time-lagged first order absorption and first order elimination. The final model includes binomial covariates correlated with clearance, absorption rate and bioavailability. The model is validated using a VPC. We split our data set in an index data set to develop a Bayesian estimator and a separated validation data set to determine its predictive performance. We are using PFIM3.2.1 in order to determine the optimal sampling schedule using the popPK parameters as estimated for the index data set. However, we are having some issues, for which we need some suggestions.
- The model has a time-lagged absorption. How can we include this in our PFIM files?
- The covariates in our final model are coded proportionally. We use an exponential random effect model (see below). How can we include our covariates in this model? Do we need to transform the value from the nonmem output file?
Nonmem: CL=THETA(1)*THETA(2)**COV
PFIM:
# covariate is additive on log parameters if exponential random effect model (Trand=2)
#-----------------------------------------------------------------------
beta.covariate<-list(COV=list(c(log(1.93))))
- We have a covariate and interpatient variability on bioavailability. How can we code this in PFIM?
- Furthermore, we developed a second model using Erlang distribution to describe the absorption. Does anybody know how to implement this in PFIM?
Thank you very much in advance for your help.
Kind regards,
Annick Rousseau and Brenda de Winter
pfim
2 messages
2 people
Latest: Sep 27, 2010
Dear Annick
There is a population optimal design email list server (PopDesign) which you
can join at this site:
http://lists.otago.ac.nz/listinfo/popdesign
This list server covers any issue relating to optimal design of population or
individual PK and PKPD experiments including questions related to the various
software (incl. pfim).
Kind regards
Steve
--
Professor Stephen Duffull
Chair of Clinical Pharmacy
School of Pharmacy
University of Otago
PO Box 56 Dunedin
New Zealand
E: [email protected]
P: +64 3 479 5044
F: +64 3 479 7034
W: http://pharmacy.otago.ac.nz/profiles/stephenduffull
Design software: www.winpopt.com
Quoted reply history
> -----Original Message-----
> From: [email protected] [mailto:[email protected]] On
> Behalf Of Annick Rousseau
> Sent: Tuesday, 28 September 2010 4:09 a.m.
> To: [email protected]
> Subject: [NMusers] pfim
>
>
>
> Dear NM-users,
>
> We developed a PK model using NONMEM for a drug using a 2-cpt model with
> time-lagged first order absorption and first order elimination. The
> final model includes binomial covariates correlated with clearance,
> absorption rate and bioavailability. The model is validated using a VPC.
> We split our data set in an index data set to develop a Bayesian
> estimator and a separated validation data set to determine its
> predictive performance. We are using PFIM3.2.1 in order to determine the
> optimal sampling schedule using the popPK parameters as estimated for
> the index data set. However, we are having some issues, for which we
> need some suggestions.
>
> - The model has a time-lagged absorption. How can we include this in our
> PFIM files?
>
> - The covariates in our final model are coded proportionally. We use an
> exponential random effect model (see below). How can we include our
> covariates in this model? Do we need to transform the value from the
> nonmem output file?
> Nonmem: CL=THETA(1)*THETA(2)**COV
> PFIM:
> # covariate is additive on log parameters if exponential random effect
> model (Trand=2)
> #-----------------------------------------------------------------------
> beta.covariate<-list(COV=list(c(log(1.93))))
>
> - We have a covariate and interpatient variability on bioavailability.
> How can we code this in PFIM?
>
> - Furthermore, we developed a second model using Erlang distribution to
> describe the absorption. Does anybody know how to implement this in PFIM?
>
> Thank you very much in advance for your help.
>
> Kind regards,
> Annick Rousseau and Brenda de Winter