Re: Differences with ADVAN3 TRANS1 and ADVAN3 TRANS4

Paul Your two models assume different inter-subject variability structures that could explain the differences. Try to run the same models with the full OMEGA matrix: then the problem would become theoretically identical (although even in this case you can see some differences that cannot be explained) Leonid -------------------------------------- Leonid Gibiansky, Ph.D. President, QuantPharm LLC web: www.quantpharm.com e-mail: LGibiansky at quantpharm.com tel: (301) 767 5566 Paul Collier wrote: > Please could someone explain why I get very different results when using ADVAN3 TRANS1 to model a data set compared with using ADVAN3 TRANS4? Using the rate constants obtained with TRANS1 for a two compartment model to compute clearance and volume terms gives different values to those obtained with TRANS4. I have tried using various initial estimates for the runs but this has not solved the problem. I have listed typical outputs from Wings for NONMEM below for each of the two ways of parameterising the two compartment model. The objective function is considerably smaller with TRANS1 ( -580 compared with -533). > > Thanks, > > Paul > > Paul S. Collier > > School of Pharmacy > > Queen's University Belfast > > Email: [EMAIL PROTECTED] > > *Using ADVAN3 TRANS1* > > THETA: ELIMINATION RATE RATE VOLUME ETA: OMEGA ERR: SIGMA run209.lst *-580.598* eval=209 sig=+3.4 sub=43 obs=184 CCIL=YNYN NVI1.1 PV1.0 > > THETA = 0.477 0.357 0.255 7.44 > > ETASD = 0.806846 0.000457165 0.00758947 1.40357 > > ERRSD = 0.242693 > > THETA:se% = 22.9 15.9 23.9 30.2 > > OMEGA:se% = 26.3 10287.1 559.0 27.7 > > SIGMA:se% = 23.4 > > MINIMIZATION SUCCESSFUL > > P VAL.: 0.75E+00 0.17E+00 0.46E+00 0.88E+00 > > MIDAZOLAM 2-COMP RATES MODEL ADDITIVE ERROR > > user 0:21.95 real 0:21.95 tcl 0:0.42 > > $PROBLEM MIDAZOLAM 2-COMP RATES MODEL EXPONENTIAL ERROR > > $INPUT ID TIME DAT1=DROP AGE DOSE=AMT RATE DV WT BUC MDV GEN > > $DATA ..\MIDAZOLAM.CSV > > $SUBROUTINES ADVAN3 TRANS1 > > $PK > > CALLFL=1 > > TVK=THETA(1) > > K=TVK*EXP(ETA(1)) > > TVK12=THETA(2) > > K12=TVK12*EXP(ETA(2)) > > TVK21=THETA(3) > > K21=TVK21*EXP(ETA(3)) > > TVV=THETA(4) > > V=TVV*EXP(ETA(4)) > > S1=V > > $ERROR > > IPRED=F > > IRES=DV-IPRED > > W=F > > IWRES=IRES/W > > Y=F*(1+ERR(1)) > > $THETA (0,0.5) > > $THETA (0,0.5) > > $THETA (0,0.5) > > $THETA (0,10) > > $OMEGA 0.01 0.01 0.01 0.01 > > $SIGMA 0.4 > > $ESTIMATION MAXEVAL=9999 PRINT=2 METHOD=CONDITIONAL INTERACTION > > *Using ADVAN3 TRANS4* > > THETA: CLEARANCE VOLUME1 INTERCOMPARTMENTAL CLEARANCE VOLUME2 ETA: OMEGA ERR: SIGMA run213.lst *-533.475* eval=380 sig=+4.5 sub=43 obs=184 CCIL=YNYN NVI1.1 PV1.0 > > THETA = 3.19 0.209 9.87 12 > > ETASD = 1.25698 0.000467974 0.00130767 0.849706 > > ERRSD = 0.283019 > > THETA:se% = 20.4 85.2 49.2 31.2 > > OMEGA:se% = 15.5 20821.9 6432.7 43.6 > > SIGMA:se% = 24.5 > > MINIMIZATION SUCCESSFUL > > P VAL.: 0.97E+00 0.93E+00 0.80E+00 0.31E+00 > > user 0:33.95 real 0:33.95 tcl 0:0.52 > > $PROBLEM MIDAZOLAM 2-COMP CLEARANCE MODEL > > $INPUT ID TIME DAT1=DROP AGE DOSE=AMT RATE DV WT BUC MDV GEN > > $DATA ..\MIDAZOLAM.CSV > > $SUBROUTINES ADVAN3 TRANS4 > > $PK > > CALLFL=-1 > > TVCL=THETA(1) > > CL=TVCL*EXP(ETA(1)) > > TVV1=THETA(2) > > V1=TVV1*EXP(ETA(2)) > > TVQ=THETA(3) > > Q=TVQ*EXP(ETA(3)) > > TVV2=THETA(4) > > V2=TVV2*EXP(ETA(4)) > > S1=V1 > > $ERROR > > IPRED=F > > IRES=DV-IPRED > > W=F > > IWRES=IRES/F > > Y=F*(1+ERR(1)) > > $THETA (0,3) > > $THETA (0,0.1) > > $THETA (0,1) > > $THETA (0,10) > > $OMEGA 0.04 0.04 0.04 0.04 > > $SIGMA 0.4 > > $ESTIMATION MAXEVAL=9999 PRINT=2 METHOD=CONDITIONAL INTERACTION > > $COVR PRINT=E