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The complexity of biology makes defining a single model system that recapitulates human disease a nearly impossible task. To overcome this inherent limitation, screening of many different systems across multiple measurement parameters enables the generation of response signatures or profiles that are more predictive and robust than measurements in single systems alone. The application of signature based discovery has included early efforts such as NCI-60, but has been limited by the amount of additional dimensional data and technical and logistical challenges that prevented collection of large scale profiles. With the recent development of large datasets of genomic characterization and annotations of cell lines, and the development of new technologies to enable measurements of profiles across hundreds of cellular systems in a cost and time efficient manner, it is now possible to routinely collect multidimensional profiles during the discovery process. Similarly, advancements in computational approaches such as the Connectivity Map allow for sophisticated queries across various profile based datasets to find correlations such as target identification and mechanisms of action. Taken together, multidimensional profile based screening can provide a wealth of information and actionable hypotheses at multiple stages of the drug development process.

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