A business model for open drug discovery
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October 30, 2018
Dr Aled Edwards, Structural Genomics Consortium, discusses the aims and benefits of open drug discovery approach
Drug Discovery1
A business model for open drug discovery
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Advanced human cellular assays
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Applying deep learning architectures to de novo molecular drug design
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Assessing and addressing biopharmaceutical aggregation
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Bispecific antibody discovery within drug discovery
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Chemical linkers in antibody drug conjugate development
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Combination treatments for rare diseases
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CRISPR in drug combination discovery
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Drug combinations in disease treatment
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Enhancing R&D
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Ensuring strong hit-to-lead discovery projects in the future
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Horizon's high-throughput platform
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How deep learning architectures have improved chemical reaction prediction
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IDO inhibitors and their pharmacological effects
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Intracellular enzyme inhibitors in small molecule drug discovery
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Investigating complex cellular systems
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Nav1.7 selective blockers and their current status of development
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Overcoming biological complexity and drug promiscuity
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TAP and its implications
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Targets for analgesic medication
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Technologies for antibody discovery
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The Academic BRIDGE paradigm
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The advantages of academic-industry drug discovery approaches
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The advantages of machine learning and artificial intelligence in the drug discovery process
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The challenges associated with immunology and immuno-oncology assays
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The challenges associated with translating drug discovery ideas to preclinical testing
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The developability issues affecting the efficacy of therapeutic monoclonal antibodies
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The difference between small molecule and antibody discovery
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The Medicines Discovery Catapult
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The Orphan Drug Act and antibiotic research
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The structural antibody database and its importance
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Using obligate bispecific antibodies
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