Sinequa accelerates drug development and clinical research with AI-powered scientific search

AI-powered search provider Sinequa is making domain-specific enhancements to its intelligent search platform for Scientific Search and Clinical Trial Data, tapping into neural search and ChatGPT capabilities for faster, more effective discovery and decisions in drug development and clinical research.

Combining the capabilities of Sinequa Neural Search—multiple deep learning and large language models for natural language understanding (NLU)—with the latest ChatGPT models through Azure OpenAI Service, Sinequa enables accurate, fast, traceable semantic search, insight generation, and summarization, according to the company.

Users can query and converse with a secure corpus of data, including proprietary life science systems, enterprise collaboration systems, and external data sources, to answer complex and nuanced questions.

Comprehensive search results with best-in-class relevance and the ability to generate concise summaries enhance R&D intelligence, optimize clinical trials, and streamline regulatory workflows.

“The ability to harness AI for scientific and clinical trial data search creates tremendous opportunities for life sciences to radically improve the speed, scale, and efficacy of clinical research and drug development,” said Clifford Cantrell, vice president, global life science practice lead and customer success, Sinequa. “Building on more than 20 years of expertise in natural language processing and as one of the first providers to apply AI to enterprise search, Sinequa continues its legacy of proven innovation by bringing generative AI capabilities to clinical research and drug development.”

For more information about this news, visit www.sinequa.com.