Austin, Texas-based Oracle has expanded Oracle Life Sciences Data Intelligence, combining real-world data, domain-trained AI and advanced analytics in a single platform for pharmaceutical research teams, the company said Sept. 23.
The platform, formerly known as Oracle Life Sciences AI Data Platform, lets researchers use natural language to build and refine patient cohorts, run outcome analyses and automate multistep research workflows with less manual coding. Its data foundation includes Oracle Health Real-World Data, which covers more than 122 million deidentified patient records.
Oracle said the AI features support cohort discovery, clinical trial recruitment, site optimization, health economics and outcomes research, market access research and evidence generation. Traceable reasoning and reviewable outputs show the analytical logic and evidence lineage behind each result.
Customers can combine their own data and third-party datasets with Oracle’s records in a governed cloud environment. The platform also connects to Oracle Cloud Infrastructure, Oracle Fusion Cloud applications and Oracle Health solutions.
“Fragmented data and disconnected workflows continue to slow the path to discovery,” said Seema Verma, executive vice president and general manager of Oracle Health and Life Sciences. “Oracle’s unique ability to offer real-world data, along with domain-specific AI tools helps enable researchers to conduct studies and explore data in natural language accelerating research from discovery to commercialization.”
Nimita Limaye, research vice president of life sciences R&D strategy and technology at IDC, said, “For the life sciences industry, AI is no longer a future ambition — it’s an operational imperative that creates value only when researchers can trust it. Oracle is bridging that gap — combining governed real-word data, domain-trained AI capabilities and advanced analytics in a single connected environment that turns complex research questions into credible evidence, faster.”
