[NMusers] Modelling IV and IP simultaneously
Dear NMusers, I'm having trouble writing the code for my model. I have IV and IP administrations data, that I would like to model simultaneously. We found out that IP was best modeled by a first order absorption, using an input compartment (DADT(1)=-KA*A(1)). At first, we used a CMT column in the dataset to indicate for each dosing event if it is IV or IP. But then, as we made the model more complicated, we realized that we couldn't use a CMT column. We study the parent compound, as well as its metabolite at the same time but the problem is we cannot put a compartment number for the metabolite's observations. This is because, given the model structure, the prediction for the metabolite concentrations is a sum of 3 concentrations in 3 different compartments (e.g. IPRED=A(6)+A(7)+A(8)). So we think that putting a compartment number for the observation would be confusing for NONMEM. What do you think? Do you see how we could model IV and IP simultaneously, without using the CMT column ? or any other solution? Thank you for your help Fanny Gallais
Re: [NMusers] Parameter uncertainty
Thank you all for your responses. It is going to be very useful for my work. Best regards, F.G. 2017-02-15 17:35 GMT+01:00 Williams, Jason <jason.willi...@pfizer.com>: > Dear Fanny, > > > > Another useful tool you may want to try is using the mrgsolve package > available in R, developed by Kyle Baron at Metrum Research Group. I have > found mrgsolve to be very efficient for PKPD simulation and sensitivity > analysis in R. There is an example of incorporating parameter uncertainty > (from $COV step in NONMEM) in Section 9 of the example on Probability of > Technical Success (link below). > > > > https://github.com/mrgsolve/examples/blob/master/PrTS/pts.pdf > > > > Best regards, > > > Jason > > > > *From:* owner-nmus...@globomaxnm.com [mailto:owner-nmus...@globomaxnm.com] > *On Behalf Of *Fanny Gallais > *Sent:* Wednesday, February 15, 2017 2:55 AM > *To:* nmusers@globomaxnm.com > *Subject:* [NMusers] Parameter uncertainty > > > > Dear NM users, > > > > I would like to perform a simulation (on R) incorporating parameter > uncertainty. For now I'm working on a simple PK model. Parameters were > estimated with NONMEM. I'm trying to figure out what is the best way to > assess parameter uncertainty. I've read about using the standard errors > reported by NONMEM and assume a normal distribution. The main problem is > this can lead to negative values. Another approach would be a more > computational non-parametric method like bootstrap. Do you know other > methods to assess parameter uncertainty? > > > > > > Best regards > > > > F. Gallais > > > > > > >
[NMusers] Parameter uncertainty
Dear NM users, I would like to perform a simulation (on R) incorporating parameter uncertainty. For now I'm working on a simple PK model. Parameters were estimated with NONMEM. I'm trying to figure out what is the best way to assess parameter uncertainty. I've read about using the standard errors reported by NONMEM and assume a normal distribution. The main problem is this can lead to negative values. Another approach would be a more computational non-parametric method like bootstrap. Do you know other methods to assess parameter uncertainty? Best regards F. Gallais
