By Sandra Blumenrath, DIA
If the steady decline in new first-in-class drugs coming to market is any indication, the current system of drug discovery is inefficient and insufficient to meet modern challenges. Automating the many decision-making processes currently carried out by researchers is hailed as the linchpin of the discovery and development of novel therapeutics, especially for difficult-to-treat conditions. In addition to data mining, another hope for AI in pre-clinical drug development is to capture patterns that are difficult to identify, simulate quantum states, or even suggest the structure of a new therapeutic molecule.
Assembling experts from the application and research side of drug discovery, the session AI in Drug Discovery and Development: Emerging Technologies and Applications addressed recent innovative ideas and tools within the realm of AI that could potentially shake up drug discovery as we know it, moving past generalist applications of AI to much more specific, purpose-built tools.