We propose an integrated application of technologies, computation and statistical methods to design experiments for examination of cellular pathways that are necessary for cell survival and that are candidates for cancer therapy. Our design combines information derived from two very different data sets: tumor screening data from over 36,000 synthetic compounds screened against over 60 tumor cell lines, and replicate microarray gene expression measurements using one cell line and one compound. Data filtering, based on restricted cellular cytotoxicity profiles from chemically similar sets of compounds, has been used to select a class of benzothiazoles for subsequent microarray gene expression measurements in the most chemosensitive tumor cell line. The results confirmed observations that P450 metabolizing isoforms, CYP1A1 and CYP1B1, are overexpressed in MCF-7 tumor cells following treatment with benzothiazole. These results are consistent with the proposed inactivity of the CYP1A1-mediated metabolism of benzothiazole and the antitumor activity of the metabolically resistant halogenated forms.