2018 Brings A Surge Of Activity In The “AI For Drug Discovery” Space

Atomwise

Atomwise, which was founded in 2012 and pioneered the use of deep neural networks for structure-based drug design, just raised $45 M round A investment to advance its AI-driven drug discovery technology. The company is focusing on addressing chemical challenges of the drug discovery process -- identifying in silico best small molecules for specific drug targets, and further computationally optimizing them into potent and safe drug candidates with optimal properties (lead optimization). The company says it currently screens 10 million small molecules each day and uses its proprietary platform AtomNet, utilizing deep learning algorithms, to analyze molecules and predict their potency as medications, toxicity, and side effects.

Atomwise now has more than 50 molecular discovery programs, allowing to rapidly improve its AI-based models, and is partnering with top pharma companies, like Merck and AbbVie, as well as prominent research institutions, including Harvard, Duke, Stanford and Baylor College of Medicine.  

Sirenas and Bristol-Myers Squibb

Sirenas, a biotech company applying machine-learning based computational approaches to discover therapeutics derived from the global microbiome, entered a multi-target research collaboration agreement with Bristol-Myers Squibb to apply its proprietary drug discovery platform against a series of undisclosed but challenging therapeutic targets. The research collaboration leverages Sirenas' expertise in applying its proprietary data mining technology ATLANTIS™ to identify potential drug candidates among Sirenas' proprietary chemical library isolated from global microbiome collections. It is important to note another area of Sirenas’ expertise -- state-of-the-art organic synthesis, which makes it possible for the company to deliver not only computational predictions but also chemical compounds with unusual nature-inspired scaffolds.

Juvenescence and Insilico Medicine