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Life Sciences

Drug Discovery & Development: Opportunities and obstacles with ML and AI development

Read insights from our Director of Business Development, Yvete Toivola, in Drug Discovery & Development. Yvete discusses the challenges of reaching the potential of AI in drug discovery, including data management and scalability. Medical imaging can fuel AI to extract fresh insights—IF leaders persist in rethinking data management practices and commit to organization-wide change.

"R&D requires a consistent approach that addresses data needs, provides tools for collaboration and creates a single source of information. A FAIR-friendly data framework does that. It allows data to be evaluated, labeled and contextualized into a reservoir of reliable information. It also alleviates the problem some organizations face when changing rules on data standardization year-over-year or between business units, which hampers data utility and creates inefficiencies. These efforts ensure that data quality remains constant, eliminating the need to start over or redefine protocols with every new project." 

Check out the article for a closer look at challenges and solutions for machine learning in drug discovery.