Oracle Life Sciences Data Intelligence1 now combines real-world data, domain-trained AI capabilities, and advanced analytics in a single connected intelligence platform, helping pharmaceutical research teams move from questions to actionable insights faster. Researchers can use natural language to explore and refine patient cohorts, perform outcome analyses, and automate multistep research workflows using a data foundation that includes Oracle Health Real-World Data comprising more than 122 million2 de-identified patient records.
The cloud native platform provides the performance and security needed to bring together customer, third-party, and Oracle Health Real-World Data in a secure environment, while giving organizations flexibility to scale as data volumes, research needs, and AI use cases evolve.
“Fragmented data and disconnected workflows continue to slow the path to discovery,” said Seema Verma, executive vice president and general manager, 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.”
With Life Sciences Data Intelligence, organizations benefit from:
Specialized AI built for life sciences workflows:
Purpose-built for life sciences, the new domain-trained AI capabilities help teams use natural-language interactions to translate business and research questions into structured analyses, refine cohorts, and automate multistep workflows while minimizing reliance on manual coding. These AI-enabled features guide researchers through common activities, including cohort discovery, clinical trial recruitment, site optimization, health economics and outcomes research, market access research, and evidence generation, helping accelerate insights across the therapeutic lifecycle. Traceable reasoning and reviewable outputs also provide visibility into analytical logic, evidence lineage, and results, supporting scientific transparency and stakeholder confidence.
Advanced analytics with traceable, transparent results:
In tandem with AI, advanced analytics help researchers perform analyses and interpret results with contextual guidance, expanding beyond basic analytics tools. Connected intelligence workflows also link models, cohorts, and insights to help reinforce consistency and repeatable results across the enterprise.
A unified, governed data foundation:
Oracle Life Sciences Data Intelligence combines a customer’s own data with Oracle Health Real-World Data which includes over 122 million longitudinal health records. The solution unifies these sources in a single, secure environment and applies enhanced data governance to help transform de-identified patient-level data into connected, decision-ready intelligence. The platform is also designed to support expansion to additional third-party datasets.
“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,” said Dr. Nimita Limaye, Research Vice President, Life Sciences R&D Strategy and Technology, IDC. “Oracle is bridging that gap — combining governed real-world data, domain-trained AI capabilities, and advanced analytics in a single connected environment that turns complex research questions into credible evidence, faster. These capabilities reflect exactly the kind of purposeful innovation that the industry needs to make smarter decisions across the therapeutic lifecycle.”
Oracle Life Sciences Data Intelligence is designed to work across Oracle’s broader, interoperable technology ecosystem, including OCI, Oracle Life Sciences, Oracle Fusion Cloud applications, and Oracle Health solutions. This connected approach can help life sciences organizations integrate data and workflows across research, clinical, safety, supply chain, and commercial operations.
