Development of a predictive model for batch membership of street samples of heroin

Street samples (n=31) of heroin were analysed by gas chromatography with fl ame ionisation detection to determine opiate, noscapine and papaverine cont ent. Using this data, the chromatograms obtained could be resolved into eig ht groups by visual examination of the data. The concentrations of opiates were significantly correlated (P<0.05) with the exception of the pairs 6-O- monoacetylmorphine/noscapine and morphine/6-O-monoacetylmorphine. This prec ludes the use of simple cluster analysis for determining and predicting the relationship of different street samples. Application of Fisher's linear d iscriminant analysis to the data set indicated that 91.9% of the samples co uld be discriminated including pairs which could not be discriminated by ey e. A blind trial (n=2) resulted in the correct assignment to street sample. Application of such methods may provide, in the future, a powerful tool fo r the prediction of batch membership of drugs at the street level. (C) 1999 Elsevier Science Ireland Ltd. All rights reserved.