The Molecular Landscape of AI/ML-Assisted Small Molecule Drug Discovery (Part III)

There have been numerous reviews on the impact of AI/ML in drug discovery looking at broad numbers, but with the volume of companies in the space, few have spelled out exactly what these companies are working on to paint a picture of what the landscape of AI/ML in small molecule drug discovery actually looks like today. 

We concluded part II of this AI/ML series by noting that it may be unfair to compare the typical AI/ML-assisted drug discovery program to the industry average program given the well-characterized nature of the targets being pursued and the existing chemical matter available. In this third article of the series, we take a broader look at companies involved in applying AI/ML to drug discovery to provide a detailed understanding of the current situation.

Whereas part II highlighted six AI/ML-focused companies with internally discovered clinical candidates from AI/ML assistance this article looks at:

  • Companies with a stated AI/ML focus whose clinical programs arose from repurposing of existing small molecules (e.g. Healx, Berg)
  • Companies not traditionally focused on AI/ML with clinical small molecule programs (e.g. Schrodinger)
  • Preclinical AI/ML-focused companies and their disclosed targets (e.g. Atomwise, Cyclica)

For a review of the history of AI/ML in drug discovery and more resources on the topic, view our reference page here, and don’t forget to check out part II of this series here

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