Phenotypic Drug Discovery – The Move from High Content to High Impact Screening
Beverley Isherwood, Associate Director & Head High Content Biology, Innovative Medicines, AstraZeneca
In recent years, phenotypic drug discovery (PDD) has received a lot of attention in industry and academia and the scientific community has started to believe that phenotypic readouts nicely complement the more conventional approaches of target-based drug discovery (TDD). As with all novel technologies, we have undergone a steep learning curve for implementing the right technologies and processes for PDD, to make best possible use of the PDD technologies, and to maximise the gain from that new hit finding paradigm.Historically, most PDD assays were based on the use of High-Content Biology (HCB) and Reporter-Gene Assays (RGA). Some of these technologies require specific equipment, such as high-throughput confocal and non-confocal microscopes to measure cell morphology, target localisation and protein translation at high throughput or eventually high-end luminescence & fluorescence based multi-well readout technologies. It is noteworthy that the readout technology in these assays has a significant effect on both throughput and output from these screening campaigns. It is relevant to use a physiologically relevant readout in a physiologically relevant cellular system to ensure good translatability of the results from phenotypic screening into downstream disease models and ultimately clinical settings.We will describe our experience over several years from using these technologies for phenotypic screening in recombinant cell lines, induced pluripotent stem cells (iPSC) and primary cells. The recent addition to the field is the use of Precise Genome Editing (PGE) with the CRISPR/Cas system to make site specific changes in the genome of these cellular models. In our presentation, we will discuss novel readout technologies such as transcriptomics and NGS, novel biological test systems such as PGE-derived iPSC, and we will give an outlook for future use of PDD in industry, academia and public-private partnerships.
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