Method verification is crucial in ensuring that a routine quantitative method remains fit for analysis. Verification is less comprehensive than validation because fewer aspects are covered. In addition, the aspects to be verified must have a significant impact on the analytical readings. In this paper, a verification process is presented in the form of tutorial in order to aid narcotics laboratories in performing this task in a more competent manner. Although heroin is used as an example in this tutorial, the overall procedure can be extended to other drug compounds as well. The procedure presented here, however, serves as a minimum requirement. Additional aspects should be included to ensure that the overall verification process is able to meet the criteria set by the clients as well as the legal practitioners. ª 2015 Hosting by Elsevier B.V. on behalf of The International Association of Law and Forensic Sciences (IALFS).

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This paper seeks to evaluate whether the chemical profiling data obtained with a constant weight approach can be used in the classification of highly cut heroin samples. A constant weight of a seized substance instead of the conventional weight equivalent to 15 mg heroin base was used to profile the manufacturing impurities. The study attempts to optimize four clustering tools using 12 impurity peaks extracted from the heroin samples (52.3% purity) analyzed at 650 mg sample weight to find the most ideal statistical techniques for sample classification. The effectiveness of four clustering tools, namely the principal component analysis (PCA), hierarchical cluster analysis (HCA), K-means clustering (KMC) and discriminant analysis (DA) was assessed using 25 heroin samples derived from five known batches. HCA and DA proved promising in clustering the related samples. Finally, only the HCA was then employed to evaluate the general relationships between 46 unknown heroin samples.

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