Original from: Labcorp
Labcorp (NYSE: LH), a global leader of innovative and comprehensive laboratory services, today announced a new AI-powered real-world data platform, designed to help researchers and biopharmaceutical companies analyze Alzheimer's disease-related data faster. Developed with Amazon Web Services (AWS) and Datavant, the platform provides access to large, diverse datasets and advanced analytics—using deidentified, privacy-protected healthcare data—designed to accelerate scientific discovery, shorten drug development timelines and improve identification of patients for clinical trial recruitment. The platform enables researchers, biopharma companies, payors and contract research organizations to generate insights in minutes that previously required months of intensive data mining.
With more than 7.2 million Americans living with Alzheimer's disease and annual care costs exceeding $380 billion in the U.S., accelerating drug development is critical. Traditionally, fragmented data and lengthy data preparation have slowed progress. Labcorp's platform addresses these challenges by leveraging standardized, direct-from-source laboratory data captured across millions of patients and advanced AI models to streamline data access and analysis. As a leader in neurology diagnostics, Labcorp offers the broadest blood-based biomarker testing portfolio for Alzheimer's disease and dementia, generating data that uniquely inform the depth, quality and scale of insights generated through this platform.
"This platform represents a powerful acceleration in Alzheimer's research," said Bola Oyegunwa, Ph.D., Labcorp's EVP and chief information and technology officer. "By combining AI, advanced analytics and the scale of Labcorp's diagnostic data, we're redefining what's possible—compressing months of manual data preparation into minutes. That shift enables researchers to focus on discovery instead of data engineering, accelerating the insights needed to drive better treatment decisions. Ultimately, this platform is about improving patient outcomes and delivering answers and hope faster for the millions of patients and families waiting for progress."
The platform represents a breakthrough in unifying healthcare research, combining Labcorp's extensive diagnostic and genomic datasets with medical claims, and, in future versions, electronic health record and social determinants of health data. Powered by advanced AI analytics, the platform can quickly identify patient cohorts, track disease progression patterns and measure treatment effectiveness across diverse populations.
Dr. Rowland Illing, chief medical officer and director, Healthcare and Life Sciences at AWS, emphasized the platform's transformative potential, "This collaboration between Labcorp and AWS shows how AI can help reduce the time from hypothesis to actionable insight from months to minutes, potentially shaving years off the drug development process. By leveraging AWS's AI services, including Amazon Bedrock to power the platform's agents and Amazon SageMaker for analyzing clinical trial and patient datasets, we're fundamentally changing the scope and scale of insights researchers can generate."
The platform's AI-powered analytics interface offers:
- Real-time, population-level analysis of treatment patterns, effectiveness and patient outcomes across diverse populations
- Characterization of patient segments tested for Alzheimer's disease
- Support for the selection of deidentified patient cohorts suitable for clinical trial recruitment based on defined inclusion and exclusion criteria
- Advanced statistical modeling tools to identify patient cohorts with unmet clinical need
The platform will complete its initial validation phase in spring 2026 and is expected to expand through 2026, incorporating additional data sources and analytical capabilities to further accelerate research insights including inflammatory diseases, cardiometabolic conditions, women's health and oncology.
This innovation extends Labcorp's broader real-world data strategy, leveraging AWS's AI-powered analytics and Datavant's privacy-preserving connectivity to enable secure, scalable analysis of de-identified healthcare data.
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