Dr. Singh: Thank you for asking.
We see great BSV in the data, although some of the etas probably will need to be fixed to zero. Also, we may want to use the same structure model for a human study. Thank you! Siwei On Mon, Apr 30, 2012 at 10:29 AM, indrajeet singh <[email protected]>wrote: > what is your rationale to use rat data for population analysis with 6 > etas? > > > On Mon, Apr 30, 2012 at 8:41 AM, siwei Dai <[email protected]>wrote: > >> Hi, NM users: >> >> I am a new NONMEM user and wish to get help from NM experts. >> >> I have a data from rats with concentration measured in both plasma and >> cerebrospinal fluid . Compared to plasma concentration, the concentration >> in brain is relatively small (up to 30 times difference). Due to the big >> range of my data, I log-transformed my data. Below is the code I used. I >> was able to get NM to run, but obvious bias existed in goodness-of-fit >> plot. I worried that there are mistakes in my code. Could anyone take a >> look of my code especially the $ERROR code to see what is wrong? >> Also, I saw in an earlier discussion on how to get additive error with >> log-transformed data, but that was for simple models. Can anybody give some >> insights on how to do it with more complex data such as the data I have? >> Thank you in advance for your time. >> >> Siwei >> >> $SUBROUTINES ADVAN6 TOL=3 >> $MODEL >> NCOMP=3 >> COMP=(COMP1) ;Central compartment >> COMP=(COMP2) ;Peripheral compartment >> COMP=(COMP3) ;Brain compartment >> $PK >> TVCL=THETA(1) >> CL=TVCL*EXP(ETA(1)) >> TVV1=THETA(2) >> V1=TVV1*EXP(ETA(2)) >> TVQ1=THETA(3) >> Q1=TVQ1*EXP(ETA(3)) >> TVV2=THETA(4) >> V2=TVV2*EXP(ETA(4)) >> TVKEQ=THETA(5) >> KEQ=TVKEQ*EXP(ETA(5)) ; Equilibration rate constant trough BBB >> TVPC=THETA(6) >> PC=TVPC*EXP(ETA(6)) ; Partition coefficient at BBB >> >> K10=CL/V1 >> K12=Q1/V1 >> K21=Q1/V2 >> >> S1=MV1 >> >> $DES >> DADT(1)=-K10*A(1)-K12*A(1)+K21*A(2)-KEQ*(A(1)*PC-A(3)) >> DADT(2)=K12*A(1)-K21*A(2) >> DADT(3)=KEQ*(A(1)*PC-A(3)) >> >> $ERROR >> >> IF(AMT.NE.0) THEN >> IPRE=LOG(1) >> ELSE >> IPRE=LOG(F) >> ENDIF >> >> CM=0 >> IF (CMT.LE.2) CM=1 >> CF=0 >> IF (CMT.GE.3) CF=1 >> YM = IPRE+ERR(1) ; Plasma >> YF = IPRE+ERR(2) ; Brain >> >> Y=CM*YM+CF*YF >> >> $EST METHOD=1 PRINT=1 MAX=9999 SIG=3 >> $THETA >> $OMEGA >> $SIGMA >> >> Here is how the data look like: >> ID TIME AMT DV_log MDV CMT >> 1 0 180 0 . 1 1 >> 1 5 0 0 0.825 0 1 >> 1 5 0 0 -0.127 0 3 >> 1 15 0 0 0.954 0 1 >> 1 15 0 0 -0.011 0 3 >> 1 25 0 0 0.937 0 1 >> 1 25 0 0 0.137 0 3 >> 1 60 0 0 1.015 0 1 >> 1 60 0 0 0.188 0 3 >> 1 100 0 0 0.567 0 1 >> 1 100 0 0 -0.311 0 3 >> 1 150 0 0 0.378 0 1 >> 1 150 0 0 -0.493 0 3 >> 1 180 0 0 -0.159 0 1 >> 1 180 0 0 -0.74 0 3 >> > > > > -- > Indrajeet Singh,PhD > Sr. Clinical Pharmacokineticist > Abbott Labs, North Chicago, IL > >
