Google Deepmind shows that AI in medicine could be more lucrative than just the next LLM



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Deepmind and Alphabet’s latest AI startup, Isomorphic Labs, aims to use AI in medicine, specifically in drug development.

Isomorphic Labs has now announced strategic research collaborations with two pharmaceutical companies, Eli Lilly and Company and Novartis. These partnerships could generate up to three billion for the startup, not including potential royalties from drug sales.

Isomorphic Labs wins deals with Eli Lilly and Novartis

Isomorphic Labs has signed an agreement with Novartis to collaborate on the discovery of small molecule therapeutics against three undisclosed targets.

The agreement includes an upfront payment of USD 37.5 million from Novartis and funding of selected research costs by Novartis. In addition, Isomorphic Labs is eligible to receive up to USD 1.2 billion in success-based milestone payments and potential royalties.

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In its first pharmaceutical partnership, Isomorphic Labs will collaborate with Eli Lilly to discover small molecule therapeutics against multiple targets. The agreement includes an upfront payment of $45 million from Eli Lilly.

Isomorphic Labs is also eligible to receive up to $1.7 billion in success-based milestone payments and tiered low double-digit royalties on net sales.

AlphaFold is the foundation of Isomoprhic Labs’ commercial growth

Isomorphic Labs uses DeepMind’s breakthrough in protein prediction with AlphaFold for drug discovery.

At the end of October, Google DeepMind and Isomorphic Labs unveiled a new version of AlphaFold, which can predict the structure of almost any molecule in the Protein Data Bank (PDB), often with atomic accuracy – an important step in understanding complex biological mechanisms in cells.

The new model goes beyond proteins and covers a wide range of biologically relevant molecules such as ligands and nucleic acids. It outperforms conventional methods in predicting protein-ligand interactions by about 20 percent, and can also predict new proteins that have not yet been structurally characterized. This could have a significant impact on drug discovery.

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