Complex heterogenous diseases of unmet need such as glioblastoma, oesophageal cancer and many neurodegenerative diseases continue to confound modern target-based drug discovery strategies. Here I describe how recent advances in multiparametric high content imaging and pathway profiling technologies support a more unbiased and comprehensive survey of pharmacological and therapeutic target classes across heterogenous cancer cell phenotypes. I present data demonstrating how combining these approaches with genetically defined cell model systems and multiparametric data analysis and machine learning tools can enable the identification of mechanism-of-action appropriately tailored to complex disease. I will present case studies describing how these methods can be frontloaded into the earliest stages of drug discovery to accelerate the identification of exciting new drug modes-of-action from phenotypic screens.
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