Real-World Data and AI Capabilities in Oracle Life Sciences Data Intelligence Help Accelerate Clinical Research and Commercialization

Oracle expands its Life Sciences Data Intelligence platform with domain-trained AI and over 122 million de-identified patient records to speed evidence generation.

Rhea-AI Summary

Oracle (ORCL) introduced enhanced Oracle Life Sciences Data Intelligence on September 23, 2026, combining real-world data, domain-trained AI, and advanced analytics in a single cloud-native platform to accelerate pharmaceutical research and commercialization.

Researchers can use natural language to define and refine patient cohorts, conduct outcome analyses, and automate multistep workflows on a data foundation that includes more than 122 million de-identified longitudinal patient records from Oracle Health Real-World Data. The platform supports secure integration of customer, third-party, and Oracle Health data with enhanced governance to transform patient-level data into decision-ready intelligence.

Specialized AI guides common life sciences tasks such as cohort discovery, clinical trial recruitment, site optimization, health economics and outcomes research, market access research, and evidence generation. Connected intelligence workflows link models, cohorts, and insights, and the system interoperates with OCI, Oracle Life Sciences, Oracle Fusion Cloud applications, and Oracle Health solutions.

Key Figures

De-identified patient records: More than 122 million records

De-identified patient records

More than 122 million records

Oracle Health Real-World Data

Key Terms

real-world data, health economics and outcomes research, pharmacovigilance

3 terms

real-world data technical

"explore real-world data and generate traceable, decision-ready evidence"

Real-world data consists of information collected from everyday sources outside of controlled experiments or official reports, such as patient records, insurance claims, or wearable device readings. For investors, it provides a more complete picture of how products and services perform in actual use, helping them make better-informed decisions based on how things work in real life rather than just in theory or controlled settings.

health economics and outcomes research medical

"site optimization, health economics and outcomes research, market access research"

Health economics and outcomes research studies the real-world costs, benefits and practical effects of medical treatments, tests or devices on patients and healthcare systems. It’s like testing a new tool in everyday conditions to see how well it works, how much it costs to use, and whether it’s worth paying for; investors watch these results because they influence pricing, insurance reimbursement, patient adoption and the long-term revenue and risk profile of health-related products.

pharmacovigilance medical

"clinical research and pharmacovigilance, throughout the therapeutic development lifecycle"

Pharmacovigilance is the process of monitoring and assessing the safety of medicines after they are on the market, ensuring that any side effects or risks are identified and managed. For investors, it matters because it helps ensure that pharmaceutical companies maintain safe products, which can influence a company’s reputation, regulatory approval, and financial stability over time.

AI-generated analysis. How Rhea-AI works. Not financial advice.

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Natural-language, domain-aware AI capabilities and expanded analytics tools enable pharmaceutical research teams to explore real-world data and generate traceable, decision-ready evidence

ORLANDO, Fla., Sept. 23, 2026 /PRNewswire/ -- 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.

To learn more about Oracle Life Sciences Data Intelligence, visit: https://www.oracle.com/life-sciences/data-intelligence/ or the Oracle Health and Life Sciences Summit online September 22–24, 2026 in Orlando, Florida. Register at: https://www.oracle.com/health/health-life-sciences-summit/.

About Oracle Life Sciences

Oracle Life Sciences is a leader in cloud technology, pharmaceutical research, and consulting trusted globally by professionals in both large and emerging companies engaged in clinical research and pharmacovigilance, throughout the therapeutic development lifecycle, including pre- and post-drug launch activities. With more than 20 years of experience, Oracle Life Sciences is committed to supporting clinical development and leveraging real-world evidence to deliver innovation and accelerate advancements—empowering the life sciences industry to improve patient outcomes. Learn more at www.oracle.com/lifesciences.

About Oracle

Oracle offers integrated suites of applications plus secure, autonomous infrastructure in the Oracle Cloud. For more information about Oracle (NYSE: ORCL), please visit us at www.oracle.com.

Trademarks

Oracle, Java, MySQL and NetSuite are registered trademarks of Oracle Corporation. NetSuite was the first cloud company—ushering in the new era of cloud computing.

¹ Solution formerly known as Oracle Life Sciences AI Data Platform (AIDP)
² All data pulled from Oracle Health Data Intelligence and current as of May 2026 and calculated using distinct person IDs, which leverage a multipoint match algorithm to account for and remove duplicates within a single health system; patients who have visited multiple health systems may appear more than once in the data.

 

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SOURCE Oracle

FAQ

AI-generated questions and answers. How Rhea-AI works. Not financial advice.

What types of research activities can Oracle Life Sciences Data Intelligence support?

The platform is designed to support cohort discovery, clinical trial recruitment, site optimization, health economics and outcomes research, market access research, and evidence generation, using natural-language interactions and advanced analytics to help translate research questions into structured analyses.

What data sources can be integrated into Oracle Life Sciences Data Intelligence?

The solution can combine a customer’s own data with Oracle Health Real-World Data, which includes more than 122 million de-identified longitudinal health records, and is designed to expand to additional third-party datasets within a single, secure, governed environment.

How does the platform address transparency and trust in AI-driven research?

The AI capabilities provide traceable reasoning and reviewable outputs that give visibility into analytical logic, evidence lineage, and results, which the company states can support scientific transparency and stakeholder confidence in AI-assisted studies.

How can interested users learn more or engage with Oracle Life Sciences Data Intelligence?

Information is available at the Oracle Life Sciences Data Intelligence webpage, and interested parties can also visit the Oracle Health and Life Sciences Summit online, held September 22–24, 2026, in Orlando, Florida, with registration available through Oracle’s event site.