Recursion Pharmaceuticals announced that it has entered into an agreement to acquire Cyclica and Valance, two preclinical startups focused on medicinal chemistry, for a total of $87.5 million. The deal adds digital chemical prediction models and additional deep learning capabilities to Recursion’s artificial intelligence (AI)-enabled drug discovery platform.
The agreed purchase prices are $40 million and $47.5 million for Cyclica and Valence, respectively. Both equity transactions are expected to close in the second quarter of 2023. His Recursion shares rose 8.5% on Monday, when the acquisition was announced, compared to the previous Friday, but the company reported his $65.3 million loss in the first quarter of 2023. doing. .
Cyclica’s MatchMaker and POEM (Pareto Optimal Embedding Model) tools will be integrated into RecursionOS. RecursionOS is Recursion’s technology platform that accelerates drug discovery using machine learning algorithms applied to biology. Cyclica’s Digital Chemistry Products, based in Toronto, Canada, adds AI-enabled proteome-wide predictive models that use AlphaFold2 structures and molecular fingerprints to its platform.
Valence brings deep learning capabilities to Recursion’s drug discovery repertoire. Based in the world’s largest deep learning laboratory in Montreal, Canada, Valence’s technology can identify drug candidates from small, noisy datasets. The team will work with Recursion’s deep learning research office, also based in Montreal.
The addition of digital chemistry and machine learning technology enhances the capabilities of Recursion’s drug discovery platform. CEO and co-founder Chris Gibson said the acquisition, combined with Recursion’s automated wet lab and computing infrastructure, will help the company leverage its technology, especially at a time when AI is becoming more prevalent in biotech. I believe that it will be firmly established as a representative example of drug discovery. .
“By rapidly accelerating our pipeline and partnerships, we look forward to proving to the world the compounding effect of this full-stack approach,” said Gibson.
