Overcoming the Data Challenges of AI-driven Drug Discovery

A human being consists of billions of cells, each with the same genetic code but interacting in a myriad ways that can eventually translate into disease. Understanding and treating that disease is, in essence, a data problem. But how do you unlock that data and how do you change an organization to systematically use that data to improve decision-making and accelerate drug discovery? In this episode, we speak with Volodimir Olexiouk, Director of Scientific Engagement and Data Science Team Lead at BioLizard, about best practices for overcoming the data challenges for AI-driven drug discovery and combining scientific expertise with data science for augmented intelligence in the life sciences. Join us as we discuss:The challenges in discerning correlation from causation and integrating domain expertiseHow bridging expertise gaps and merging data silos in pharmaceutical companies radically improves drug-discovery processes The promise AI holds for swifter and more effective responses to future pandemics