Scientist.com, the world’s leading marketplace for biopharma research, today announced the launch of a new large language model (LLM)-powered research assistant called Elisa, named in homage to a widely used research assay and to ELIZA, an early 1960s chatbot. Elisa is the newest addition to a suite of proprietary AI-powered apps created by Scientist.com to improve and accelerate drug research. Marketplace users can now benefit from a powerful, scalable, and intuitive LLM assistant that understands the nuances of pharmaceutical research and has been trained on Scientist.com’s public data sources.
“Elisa is a bridge between advanced technology and our customers, providing them with instant access to marketplace information and a conversational interface that understands their research needs,” said Chris Petersen, Founder and CTO of Scientist.com. “It’s the latest in a series of LLM-powered tools we’ve built to help life science researchers run their drug discovery programs faster and at lower cost.”
Elisa addresses three key challenges for pharma and biotech companies integrating large language models into their operations:
1. It guarantees complete privacy and confidentiality of all data.
2. It provides a cost-efficient solution with the capabilities and flexibility of high-end platforms like Azure or Amazon.
3. It eliminates the need for extensive technical expertise to develop and operate a private LLM on your own infrastructure.
Other LLM-enabled tools on the Scientist.com marketplace help marketplace users negotiate pricing with suppliers, respond quickly to supplier messages, find services and products, and understand legal agreements.
The company also uses machine learning algorithms trained on nearly a decade 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 forecast supplier performance once the research project is initiated. These include the Tumor Model FinderTM, which compares DNA sequencing data on 10,000 oncology models to help researchers identify and purchase the most appropriate model.
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