Target Discovery

A major use of high-content technologies is to identify novel targets for therapeutic intervention. Disease association studies using single-nucleotide polymorphism

(SNP) whole-genome arrays can yield numerous potential targets that may be prioritized through pathway interrogation, mechanistic studies, and analysis of clinical specimens for gene or protein expression. In cancer, the development of somatic mutations leads to additional complexity in target discovery as the genomic characteristics of the tumor are known to change over time.

Clinical association data suggesting mechanistic involvement of a target with a certain patient subset should guide the early Pgx strategy. Depending on the strength of association, knowledge of variable target expression might immediately trigger plans to codevelop a diagnostic tool to identify suitable patients for treatment (9). Development of cetuximab for tumors overexpressing epidermal growth factor receptor (EGFR) followed this paradigm. Alternatively, a plan to stratify patients on the basis of a Pgx test result would allow the association with response to being tested prospectively. Either way, a fit-for-purpose diagnostic test for the candidate marker will be needed in early clinical development. In cases where the target is related to a clinical disease end point, qualified assays may already be available.

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