A historically significant milestone has just been reached by Oxford, UK-based Exscientia, which used its artificial intelligence (AI)-based drug discovery platform Centaur Chemist™ to deliver the first drug candidate in the framework of their multiyear collaboration with GSK. This AI-derived small molecule is a highly potent in vivo active substance targeting a novel pathway for the treatment of chronic obstructive pulmonary disease (COPD). The milestone is among first early successes in drug discovery associated with the recent adoption of novel machine learning/AI methods and workflows.
Drug Discovery Insights
Recently D.G.Brown and J.Boström of AstraZeneca published an insightful analysis, where they reviewed lead generation research strategies behind 66 small molecule clinical candidates published over 2016-2017 in Journal of Medicinal Chemistry.
Below is a brief summary of some key statistics and ideas outlined in the work (I encourage reading the original paper, it contains a ton of valuable insights and a strong list of references).
Effective drug discovery begins with the right assay, but the definition of "right" will shift as technology advances. More often than not, "right" is the product of tribal knowledge, namely the traditions of one's close peer group, study lineage and corporate culture. Instead, the right assay should be a fit-for-purpose application born of a broader, continuously updated, and unbiased consensus. As Steve Hamilton, aka The Lab Man, at the Society for Laboratory Automation and Screening (SLAS) has often stated in his blog posts, "developing assays – properly – is the cornerstone for life sciences R&D."
The16th century alchemical and 19th century science fiction revival of a miniature human being in a test tube is undergoing a radical upgrade. Microfluidics, complex organoid cultures, and nanodetection of phenotypic and genomic outputs are turning the metaphor into a reality to be seriously reckoned with in drug R&D. Here are recent highlights from the (mostly) open access literature, which should bring drug hunters up to speed
The question is often raised, but the answer remains to be uncovered because the definition of drug "target" continues to evolve. Historical conceptualization is focused on catalytic sites, substrate binding sites, or epigenetic modification sites. Current understanding that protein-protein interactions are druggable, along with the emerging realization that "nodes" in signaling pathways and biological networks themselves can be manipulated with small molecules in non-traditional ways, has opened up new targeting options. This review is intended to provide a status update, and you can also access a list of 36 actionable web resources for target hunting.