Dr. Matthew Lewis discusses why data quality is fundamental to metabolomics research, how AI‑ready workflows and upgradeable ...

Nearly 80 percent of organizations now use AI in at least one core business process, according to McKinsey, yet widespread adoption has surfaced a persistent problem: a deep shortage of professionals ...

Overview: The global Artificial Intelligence (AI) in drug discovery market is projected to grow at a rate of 25-30% over the ...

Global RBM requires interoperable architectures across EDC, IRT, eCOA, labs, imaging, EHR, and safety systems, but inconsistent CDISC/HL7 FHIR adoption and proprietary APIs impede near–real-time ...

AI is not overhyped. The potential requires equal attention to the less glamorous but more important role of data management.

I asked 5 data leaders about how they use AI to automate - and end integration nightmares ...

MCP registries are emerging as the new integration catalog for AI agents. Building one for the enterprise requires semantic discovery, strong governance, and developer-friendly controls.

Debuting in Asus’ exciting 16-inch Zenbook A16, Qualcomm's 2026 flagship processor looks like a benchmark bombshell ready to ...

Here is a sneak peek at the AI content in EDA and how it comprises four camps, all missing the real opportunity.

AI does not need to become self-aware to create serious danger. The real risk comes from access, autonomy, poor goal setting, ...