article

AI-driven automated chemistry as a tool to accelerate drug discovery

Typically, early drug discovery campaigns start with the screening of chemical libraries to identify candidate chemotypes modulating a particular target and/or phenotype. Success of the primary screening depends on multiple factors related to both biology and chemistry. These include the target’s druggability, sensitivity and specificity of assay system, composition and diversity of chemical libraries, number of screened compounds, etc.

AI in drug discovery chemistry

SINCE every project has cost constraints, the chemical libraries cannot cover the entire chemical space of up to 1060 potentially drug-like small molecules.1 Moreover, chemical library size ranges are often between tens of thousands to hundreds of thousands, which further complicates the search for new prospective chemotypes in such narrow chemical space. The recent advances in chemistry automation could help to overcome this limitation and establish the process of new bioactive chemical discovery.

The rest of this content is restricted - login or subscribe free to access

drug target review 1 2019 coverThank you for visiting our website. To access this content in full you'll need to login. It's completely free to subscribe, and in less than a minute you can continue reading. If you've already subscribed, great - just login.

Why subscribe? Join our growing community of thousands of industry professionals and gain access to:

  • quarterly issues in print and/or digital format
  • case studies, whitepapers, webinars and industry-leading content
  • breaking news and features
  • our extensive online archive of thousands of articles and years of past issues
  • ...And it's all free!

Click here to Subscribe today Login here

 


Send this to a friend