mixture model coding

Dear All, I am trying to model a tumor size data at different time points using NONMEM. There is high variability in baseline tumor size and their might be sub-populations in the dataset with different distribution for size progression. For example, in many cases the baseline tumor size is around 100- 200 units, and there are few patients with baseline size around 500 - 700 units. Due to this high variability I want to try a mixture model - can anybody suggest on how to do it ? I have listed the initial code that I used. $PROB run# 101 $DATA V2.csv IGNORE C $INPUT C ID TIME TYPE DV(SIZE) MDV GENDER AGE $PRED BASE= THETA(1)*EXP(ETA(1)) ;baseline tumor size PR= THETA(2)*EXP(ETA(2)) ;linear tumor progression TR=THETA(3)*EXP(ETA(3)) ;treatment effect EFF1 = BASE*EXP(-TR*TIME) EFF2 = PR*TIME IPRED= EFF1+EFF2 Y=IPRED + ERR(1) $THETA (0,100) ; baseline (0.001,0.5 ) ; progression (0.01, 0.06, 1) ; treatment $OMEGA 0.5 ; ETA-Baseline 0.2 ; ETA-PR 0.2 ; ETA-treatment $SIGMA 20 ; ERR-add ---------- Thanks, Gaurav -- Gaurav Bajaj Postdoctoral Fellow, Pharmacometrics Laboratory for Applied PK/PD Clinical Pharmacology & Therapeutics The Children's Hospital of Philadelphia