Scientist.com, the world’s leading marketplace for biopharmaceutical research, announced the launch of a new Large Language Model (LLM)-powered research assistant called Elisa, named in reference to a widely used research test and ELIZA, a chatbot of the early 1960s. Elisa is the latest addition to a suite of proprietary AI-powered applications developed by Scientist.com to enhance and accelerate drug discovery. Marketplace users can now benefit from a powerful, scalable and intuitive LLM assistant that understands the intricacies of pharmaceutical research and is trained on Scientist.com’s public data sources.
“Elisa is a bridge between advanced technology and our customers, giving them instant access to marketplace information and a conversational interface that understands their research needs,” said Chris Petersen, Founder and CTO of Scientist.com. “It is the latest in a series of LLM-powered tools we have developed to help life science researchers execute their drug discovery programs faster and at a lower cost.
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Elisa addresses three key challenges for pharmaceutical and biotech companies integrating large language models into their processes:
1. It guarantees the complete protection and confidentiality of all data.
2. It offers a cost-effective solution with the capabilities and flexibility of high-end platforms such as Azure or Amazon.
3. It eliminates the need for extensive technical expertise to develop and run a private LLM on your own infrastructure.
Other LLM-enabled tools on the Scientist.com marketplace help marketplace users negotiate prices with vendors, respond quickly to messages from vendors, find services and products, and understand legal agreements.
The company also uses machine learning algorithms trained on nearly ten years of marketplace data to create proprietary predictive models that help researchers find and evaluate the best technology and labs for their research needs, as well as predict vendor performance once the research project has begun. This includes the Tumor Model Finder TM , which compares DNA sequencing data from 10,000 oncology models to help researchers identify and purchase the most appropriate model.
Source: Businesswire
