Opportunities and challenges in phenotypic drug discovery: an industry perspective

By John G. Moffat, F. Vincent, Jonathan A. Lee, J. Eder, M. Prunotto. Nature reviews. Drug discovery, 2017

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Rethinking drug design in the artificial intelligence era (2019, background): “…to the availability of data for model building is the fact that, in many cases, experiments do not generate data that can be easily translated to a single number like a biochemical dissociation constant ( K d ) or a cellular effective concentration for half-maximum response (EC 50 ) value 51 .”
Utilizing graph machine learning within drug discovery and development (2021, background): “It has been suggested that PDD could provide the new paradigm of drug design, reducing costs substantially and increasing productivity [169].”