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
