Real-World Data & Market Intelligence - software & AI news

Daily news on software, AI, and companies shaping real-world data & market intelligence.

Showing 27 results
A blood sample in a lab setting

Apr 29, 2026

Labcorp Stock (US50540R4092): AI-Powered Platform Launch Accelerates Alzheimer's Research

Labcorp has launched an AI-driven real-world data platform in collaboration with AWS and Datavant, aimed at accelerating Alzheimer's research. This initiative, announced on April 29, 2026, positions Labcorp as a frontrunner in utilizing AI for clinical data analysis, appealing to U.S. investors interested in biotech innovations.The new platform enhances Labcorp's capabilities in real-world data analysis, which is crucial for advancing Alzheimer's research. This move aligns with a broader industr
Flat silhouette of a data chart representing oncology data monetization

Apr 29, 2026

TEM: Data Partnerships And Backlog Will Support Future Oncology Data Monetization

Recent analysis on Tempus AI indicates a mixed outlook, with price targets adjusting slightly to $72.40, reflecting updated revenue growth models and profit assumptions following Q4 results and ongoing partnerships.Analysts are divided in their views on Tempus AI, with some raising targets while others adopt a more cautious stance. The focus is primarily on the company's ability to execute partnerships and monetize its data, which are seen as vital for long-term growth. Bullish analysts highligh
An open medical file on a desk in a dimly lit office, emphasizing patient data.

Apr 25, 2026

SEQSTER CEO Ardy Arianpour on AWS Bio Discovery, fragmented health records and AI drug discovery’s missing patient layer

Ardy Arianpour, CEO of SEQSTER, highlights the vital role of patient-level data in AI-driven drug discovery, particularly in light of Amazon's recent Bio Discovery initiative.As major tech companies increasingly venture into healthcare, Amazon's Bio Discovery emphasizes the importance of integrating advanced AI with real-world patient data. Arianpour argues that while AI can generate valuable molecular hypotheses, the absence of comprehensive patient data limits its effectiveness. He stresses th