AWS partners with EvolutionaryScale following its $142M raise

Amazon Web Services (AWS) announced it is collaborating with EvolutionaryScale, an AI company focused on biology, to give scientists and researchers access to the startup’s ESM3 language models via AWS to advance drug discovery by allowing for the creation of new proteins.

Yesterday, EvolutionaryScale, founded by former researchers at Meta’s AI research lab, announced it secured $142 million in seed funding led by Nat Friedman, Daniel Gross and Lux Capital with participation from AWS and the venture capital arm of NVIDIA

EvolutionaryScale’s ESM3 AI model, which the company also recently released, allows scientists and researchers to create entirely new complex multi-domain proteins from scratch, incorporate antibody understanding and create protein design workflows.

“Trained on multiple modalities and billions of protein sequences spanning 3.8 billion years of evolution, ESM3 can understand complex biological data from various sources and generate entirely new proteins that have never existed in nature,” Amazon Web Services’ Matt Wood, VP of artificial intelligence products, wrote in a statement. 

“ESM3’s powerful capabilities…allow scientists and researchers to take a novel ‘programmable biology’ approach, potentially reducing the time and cost of bringing new therapeutics to market by years and billions of dollars.”

ESM3 includes three proprietary models and one open-source model. The open-source version is available to AWS customers on Amazon SageMaker and AWS HealthOmics. Later this year, it will be made available via Amazon Bedrock. 


Earlier this month, Google announced the creation of an LLM it created for drug discovery and therapeutic development dubbed Tx-LLM.

The therapeutics-focused large language model was fine-tuned from PaLM-2, the tech giant’s generative AI technology that uses Google’s LLMs to answer medical questions. 

The LLM constructs the Therapeutics instruction Tuning (TxT) collection by interleaving free-text instructions with representations of small molecules, such as SMILES strings for small molecules. 

SMILES, or Simplified Molecular Input Line Entry System, is a typographical method using printable characters representing molecules and reactions. 

TxT was used to prompt and fine-tune Tx-LLM to solve classification, regression and generation tasks involved in drug discovery and therapeutic development.

The HIMSS AI in Healthcare Forum is scheduled to take place September 5-6 in Boston. Learn more and register.



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