Hi, Thank you for your reply. You mentioned that you cannot see from the data whether they correspond to the indirect response model with inhibition. Can you advise me how I can infer from the data what kind of model this PD data should correspond to?
And if it's not an indirect response model, what other models do u suggest I use? On Sat, Feb 12, 2011 at 11:56 PM, Leonid Gibiansky < [email protected]> wrote: > The code looks OK, but I cannot see from the data whether they indeed > correspond to the indirect response with inhibition. Looks like random > oscillations to me. This could be a reason for error messages. > > I would try to fix ETA_Kin or ETA_Kout to zero and use only additive (or > proportional) error. Also, it will not help convergence but it is more > mechanistic to use > > CONC = A(2)/S2 > INH =CONC/(IC50+CONC) > > Then IC50 will be in concentrations rather than in amounts. > > Also, TOL=3 is to small. Try to use TOL=6 at least (better 7 or 8). Same > for PK: TOL=3 is not good for the final model. > > Regards > Leonid > > -------------------------------------- > Leonid Gibiansky, Ph.D. > President, QuantPharm LLC > web: www.quantpharm.com > e-mail: LGibiansky at quantpharm.com > tel: (301) 767 5566 > > > > > On 2/11/2011 10:35 AM, xin yi wrote: > >> Hi all, >> >> I'm new to nonmem and would be grateful for some pointers and help. I'm >> trying to do a pk-pd sequential modelling. I have modelled the PK data >> but I've encountered problems with PD. My PD model is a indirect >> inhibition response model. I have tried to change my initial estimates >> reduce the number of parameters in the model, but nothing seem to get me >> a good convergence. At different times, NONMEM gives me different error >> messages such as "parameter estimates near its boundary", "Minimisation >> successful. However problems occured with the minimization"(blank >> entries for omega or sigma estimates in the results file) ///or the "r >> matrix is algorithmically singular and non-positive definite". I have a >> few questions: >> >> 1) Are there any errors in the way I input my control and data file? >> 2) Under $ERROR in the control file, did I define it correctly with >> EFF=A(4), Y//=EFF+EFF*ERR(1)+ERR(2)/? Or should it be IPRED=F, >> Y=F+F*ERR(1)+ERR(2). >> 3) Why are they no estimates for sigma and omega in the results file? I >> have been constantly changing my initial estimates for omega and sigma >> but they always give me nil results. >> >> I appreciate any help on this matter. Thanks! >> >> Regards, >> X.Y. Ng >> / >> *This is an example of my control file:* >> >> $PROB RUN# pd_3_advan6 >> $INPUT ID TIME DV AMT CMT ADDL II MDV V2I V3I QI CLI KAI >> >> $DATA FINAL2.2.CSV IGNORE=C >> $SUBROUTINES ADVAN6 TRANS1 TOL=3 >> $MODEL >> COMP=DEPOT >> COMP=CENTRAL >> COMP=PERIPH >> COMP=EFFECT ;$MODEL defines the no of compartments in the model >> >> $PK >> >> V2=V2I >> V3=V3I >> Q=QI >> CL=CLI >> KA=KAI >> S2=V2 >> S3=V3 >> KIN=THETA(1)*EXP(ETA(1)) >> KOUT=THETA(2)*EXP(ETA(2)) >> IC50=THETA(3)*EXP(ETA(3)) >> F4=KIN/KOUT >> >> $DES >> DADT(1)=-KA*A(1) >> DADT(2)=KA*A(1)-Q/V2*A(2)+Q/V3*A(3)-CL/V2*A(2) >> DADT(3)=-Q/V3*A(3)+Q/V2*A(2) >> INH =A(2)/(IC50+A(2)) >> DADT(4)=KIN*(1-INH)-KOUT*A(4) >> >> $ERROR >> CP2=A(2)/S2 >> CP3=A(3)/S3 >> ;IPRED=F >> EFF=A(4) >> Y=EFF+EFF*ERR(1)+ERR(2) >> >> $THETA (0,0.281) ;POPKin >> $THETA (0,0.003) ;POPkout >> $THETA (0,2) ;POPIC50 >> >> $OMEGA 0.003 ;BSV Kin >> $OMEGA 0.003 ;BSV Kout >> $OMEGA 0.003 ;BSV IC50 >> >> $SIGMA 0.01 ;ERRCCV >> $SIGMA 0.0015 ;ERRADD >> >> $ESTIMATION METHOD=1 INTERACTION NOABORT MAXEVAL=9990 PRINT=10 POSTHOC >> $COVARIANCE >> $TABLE ID TIME DV AMT CMT NOPRINT ONEHEADER FILE=pd_3_advan6.TAB >> >> *and an example of my data:* >> >> / >> CID TIME DV AMT CMT ADDL II MDV V2I >> V3I QI CLI KAI >> 101 0 0 100 1 2 8 1 44.55 >> 11.78 1.07 3.37 0.62 >> 101 0 0 1 4 0 0 1 44.55 >> 11.78 1.07 3.37 0.62 >> 101 3 243 0 4 0 0 0 44.55 >> 11.78 1.07 3.37 0.62 >> 101 7 293 0 4 0 0 0 44.55 >> 11.78 1.07 3.37 0.62 >> 101 11 261 0 4 0 0 0 44.55 >> 11.78 1.07 3.37 0.62 >> 101 15 260 0 4 0 0 0 44.55 >> 11.78 1.07 3.37 0.62 >> 101 19 277 0 4 0 0 0 44.55 >> 11.78 1.07 3.37 0.62 >> 101 23 290 0 4 0 0 0 44.55 >> 11.78 1.07 3.37 0.62 >> 101 35 233 0 4 0 0 0 44.55 >> 11.78 1.07 3.37 0.62 >> 101 39 271 0 4 0 0 0 44.55 >> 11.78 1.07 3.37 0.62 >> 101 43 274 0 4 0 0 0 44.55 >> 11.78 1.07 3.37 0.62 >> 101 47 276 0 4 0 0 0 44.55 >> 11.78 1.07 3.37 0.62 >> >> / >> / >> >
