ARTICLE | Tools & Techniques

Hopes in the machine

How machine learning is being used in drug R&D

January 21, 2017 2:16 AM UTC

Applying machine learning tools to drug R&D could usher in a new era of effective therapies targeting causative disease drivers, higher success rates in clinical trials and real-world tools to manage adherence, prevent adverse events and reduce total healthcare costs.

Biopharma companies have been working at mining big data since the genomics era began, but traditional data mining parses only one type of data at a time to yield correlations. For example, mining sequencing data can reveal a correlation between a patient population and a disease target or mutation. But it doesn’t reveal whether the mutation is a causative agent in pathogenesis, or its relationship to other factors that affect the safety and efficacy of targeted drugs in different patients...