Re: Build a cell-cycle based tumor growth model

Feng, There is no need to worry about compartment numbers to match your observations. The CMT data item is only needed when you have to identify a compartment for an AMT. With NONMEM VI it is no longer necessary to use CMT and AMT to initialize compartments. If you are still using NONMEM V it is time you updated your system. I use my own named data item called DVID to identify different types of observations e.g. $INPUT ID TIME DVID DV L2 where DVID could range from 1 to 4 to define the 4 different observations. You could use it in $ERROR like this. IF (DVID.EQ.1) THEN Y=A(1)+EPS(1) ENDIF ... IF (DVID.EQ.4) THEN Y=A(4)+EPS(4) ENDIF I am not really sure how to reply to your other questions because I dont know which things you are measuring. Do you have observations of G1, S, G2 and M? Do you also have a measurement of tumour size? Please give us an idea of what differential equations you think you need to describe the biomarkers you mention. Nick Feng Yang wrote: > Dear nmusers: > > Recently I am trying to build a cell-cycle based tumor growth model, i.e. tumor size = G1+ S + G2 + M. Meanwhile, I have quite a few simultaneous biomarkers to characterize the cycle behaviors. Those biomarkers could be calculated based on the population of G1, S, G2, and M. I have the following puzzles needed to be addressed: > > 1) In my data file, what is the CMT number I should give to those observations (such as tumor size and many biomarkers)? By the way, I need CMT to specify/initialize the corresponding compartment. Since I am not quite sure how to use L2 and PCMT, I tried many times, all failed except the following foolish way: > > I create one more compartment to hold the tumor size: > DADT(iTUMROR) = DADT(iG1) + DADT(iS) + DADT(iG2) + DADT(iM) > > and in my data file, I put the CMT compartment created (iTUMOR) into the observation of tumor size. > > However, for all other biomarkers, there is no way to write this kind of DADT equations. How could I solve this in a smart way? > > 2) Since some biomarker data are collected based on certain time point, saying t0. In other words, they are relative fold-changes compared to the vehicle at t0. Therefore, I need to save the intermediate population of G1, S, G2 and M at t0, as constants, which will be used to scale the later-on populations so that the model predictions are comparable with the observations. > > However, in the both block $DES and $ERROR, there is no way to save these intermediate populations as global variables or constants. I guess, I have to use MSFO to separate the simulation to many sections? But it am not sure how to do it. > > Your thoughts and feedback are really appreciated! Thanks a lot! > > Feng -- Nick Holford, Dept Pharmacology & Clinical Pharmacology University of Auckland, 85 Park Rd, Private Bag 92019, Auckland, New Zealand [EMAIL PROTECTED] tel:+64(9)373-7599x86730 fax:+64(9)373-7090 http://www.fmhs.auckland.ac.nz/sms/pharmacology/holford