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Hi,
Can anybody provide me nonmem script for simultaneous fit of IV and Oral data (population pharmacokinetic modeling) to derive parameters ka and F ?
with best regards,
Raghav
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Raghav,
When first learning to use NONMEM I had the same question. This is a very common question, and the solution is not always obvious to the new NONMEM user. The solution is to use ADVAN2 and perform a little "trick" with dosing. I have a complete description of the solution, why you need to use ADVAN2, and sample files (dataset and control stream) on my blog (http://wp.me/p1fZzZ-2E). Feel free to use these sample files to help solve your problem.
Best of luck!
Nathan
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Nathan,
Thanks for your reply and is useful for me althogh i am not using as such NONMEM software but instead using phoenix NLME (nonlinear mixed effects) software for population PK modeling. Can these rules be extrapolated to same?
I observed a change in values when analyzed individually both IV and Oral compared to simultaneous fit. How this is answered?
Regards,
Raghav choudary.
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Raghav,
There are many experts with Phoenix NLME that follow this board (e.g. Dan Weiner, Simon Davis) who can answer you on how to set up your control stream and data for that software package. However, the idea I presented in my blog post (http://blog.learnpkpd.com/) would still apply. You will use an oral compartmental model to fit both the IV and oral simultaneously. The key is to administer the IV dose to the central compartment rather than the default depot compartment (gut).
You will see differences between the parameter estimates from fitting the IV and oral data separately and simultaneously. A similar result would arise if you calculated the average weight of people in your office by sampling 20 people, then you calculated the average weight again by sampling 100 people. You would get 2 different estimates for average body weight.
In your case, the difference in parameters will arise because you are using different amounts of data to fit the parameters. When simultaneously fitting the IV and oral data, the estimates of CL and V are based on both the IV and the oral data. However, when you fit the IV and oral data separately, the estimates of CL and V are only based on the specific data used.
Best of luck,
Nathan
-- Nathan S. Teuscher, PhD
Founder, PK/PD Associates
www.learnpkpd.com
blog.learnpkpd.com
nathan.-at-.learnpkpd.com
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Hi Nathan,
Sorry to come to this discussion a little late - I'm not really a population expert but thanks for your referral ;0) - is it OK if I link from your blog entry to the Pharsight NLME forum www.pharsight.com/extranet where I can post up an example project where I've used your data and NM script to compare and contrast with NLME in a single Phoenix workflow? Raghav,
I think you'll find it quite easy to convert a built in model to do this in NLME. Here are the steps I would suggest to see how to modify an existing model to add another dosepoint;
1) Select Parametisation of Clearance.
2) Choose Absorption of Extravascular (leave the number of compartments at 1 if using Nathan's example iv-oral-sample.csv)
3) Now select "Edit as Graphical" and under Abs compartment options in the Structural tab check the box for bioavailability.
3) Now select "Edit as textual" and simply and a second dosepoint line for A1
test(){
deriv(A1 = - (Cl * C) + (Aa * Ka))
urinecpt(A0 = (Cl * C))
deriv(Aa = - (Aa * Ka))
C = A1 / V
dosepoint(Aa, bioavail = (F))
dosepoint(A1)
error(CEps = 0.2)
observe(CObs = C * (1 + CEps))
stparm(V = tvV * exp(nV))
stparm(Cl = tvCl * exp(nCl))
stparm(Ka = tvKa * exp(nKa))
stparm(F = tvF * exp(nF))
fixef(tvF = c(, 0.5, ))
fixef(tvV = c(, 6.2, ))
fixef(tvCl = c(, 11, ))
fixef(tvKa = c(, 12.5, ))
ranef(diag(nV, nKa, nCl, nF) = c(0.2, 0.2, 0.2, 0.2))
}
4) Set up your input mappings (note I made a minor modification to the data in my workflow by creating separate columns for IV and Oral doses to keep the code simple)
Sort : ID
Aa : ORALamt
Aa Rate :
A1 : IVamt
A1 Rate :
Time : TIME
CObs : DV
5) Optionally use the Initial estimates tab (see screen shot).
[Deleted - sorry no atachments - db]
6) Choose your desired algorithm and execute. Since there are only two profiles here I used Naive-pooled in Phoenix but with more data you could have selected from the others e.g. FOCE-ELS or Lindstrom Bates, Laplacian, ITS2-EM, Non-parametric options etc
Note the code as compiled automatically has statements for random effects i.e. ETAs but this dataset is too small to be meaningful, hence I ran as NaivePooled so they are ignored, once you have more data and select another engine then like FOCE then they will be estimated. One final point to watch is Phoenix estimates Std Deviation as opposed to Variance.
Please post to the Pharsight Product discussion forum - www.pharsight.com/extranet if you'd like to discuss this further and I will try to post up an example project.
Best regards,
Simon.
--
Simon.Davis.-a-.certara.com
Senior Scientific Consultant
Pharsight- A Certara(TM) Company
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