Normally, the NONMEM reserved variable PRED will be automatically calculated for the user when the data is the typical normally distributed type. However, when data are modeled with a user specified likelihood (F_FLAG>0), the PRED value will be set to an uninformative value. To get around this,
In $ERROR block, right after you define IPRED, insert IF(COMACT==1) PREDV=IPRED and add PREDV as one of your table items. During COMACT=1, your model will be evaluated at ETA=0, and you can use that to pick out IPRED evaluated at ETA=0, which is equivalent to the normal meaning of PRED. Robert J. Bauer, Ph.D. Senior Director Pharmacometrics R&D ICON Early Phase 820 W. Diamond Avenue Suite 100 Gaithersburg, MD 20878 Office: (215) 616-6428 Mobile: (925) 286-0769 [email protected]<mailto:[email protected]> www.iconplc.com<http://www.iconplc.com/> From: [email protected] [mailto:[email protected]] On Behalf Of Andrew Tse Sent: Friday, February 22, 2019 1:23 AM To: [email protected] Subject: [NMusers] Strange PRED prediction in SAEM with M3 BQL handling Dear all, I am running SAEM with M3 BQL handling method via PsN but having some strange PRED values in mytab table if someone can shed some light: I have tried using FOCE (excluding BQL data) & SAEM (excluding BQL data) both have normal looking fitting with data in individual plots. Once I have coded SAEM with M3 codes and include BQL data it showed very strange PRED vs time plots (eg. 100 times over prediction at BQL time point). IPRED had normal results. Here are the control stream that I have used: $PK TVCL=THETA(1) MU_1=LOG(TVCL) CL=EXP(MU_1+ETA(1)) TVV2=THETA(2) MU_2=LOG(TVV2) V2=EXP(MU_2+ETA(2)) TVQ=THETA(3) MU_3=LOG(TVQ) Q=EXP(MU_3+ETA(3)) TVV3=THETA(4) MU_4=LOG(TVV3) V3=EXP(MU_4+ETA(4)) K23=Q/V2 ;Distribution rate constant K32=Q/V3 ;Distribution rate constant KA=0 A_0(1)=0 A_0(2)=0 A_0(3)=0 $DES DADT(1)= -KA*A(1) DADT(2)= -CL*A(2)/V2-K23*A(2)+K32*A(3) DADT(3)= K23*A(2)-K32*A(3) $ERROR IPRED=A(2)/V2 W=SQRT(THETA(5)**2+((THETA(6)*IPRED)**2)) IF (LIMI.EQ.1) LIM= 0.05 ;BATCH 1 IF (LIMI.EQ.2) LIM= 0.01 ;BATCH 2 IF (LIMI.EQ.3) LIM= 0.025 ;BATCH 3 IF(BQL.EQ.0) THEN F_FLAG=0 Y=IPRED+W*ERR(1) ELSE F_FLAG=1 ;BQL so Y is likelihood Y=PHI((LIM-IPRED)/W) ENDIF IWRES=(DV-IPRED)/W IRES=DV-IPRED My question is that whether there is error in my M3 $ERROR model? or whether PRED values for BQL means something else other than prediction for BQL data? Thanks a lot. Kind regards, Andrew Tse Research Pharmacist <br /><br /> ICON plc made the following annotations. ------------------------------------------------------------------------------ This e-mail transmission may contain confidential or legally privileged information that is intended only for the individual or entity named in the e-mail address. If you are not the intended recipient, you are hereby notified that any disclosure, copying, distribution, or reliance upon the contents of this e-mail is strictly prohibited. If you have received this e-mail transmission in error, please reply to the sender, so that ICON plc can arrange for proper delivery, and then please delete the message. Thank You, ICON plc South County Business Park Leopardstown Dublin 18 Ireland Registered number: 145835
