AI’s preference for drugs with a strong online presence may cost millions
Peer-Reviewed Publication
This month, we’re focusing on artificial intelligence (AI), a topic that continues to capture attention everywhere. Here, you’ll find the latest research news, insights, and discoveries shaping how AI is being developed and used across the world.
Updates every hour. Last Updated: 2-Nov-2026 20:15 ET (3-Nov-2026 01:15 GMT/UTC)
Large language models overwhelmingly select drug recommendations based on a small number of drug products, often favoring brand-name products, those highly visible in Google searches, or with dedicated Wikipedia pages. This bias would increase drug acquisition costs by millions of dollars compared with physicians’ typical recommending patterns.
Lehigh University PhD student Saskia Putri worked with Siemens through the Pasteur Partners PhD (P3) Program to explore more resilient and sustainable power systems for AI data centers. Her research focused on managing rapid fluctuations in electricity demand, integrating renewable energy and storage, and improving grid stability, while also giving her firsthand experience with industrial research and product development.
Feeding an expanding global population under extreme climate threats requires a revolution in crop improvement. In a new review in SCIENCE CHINA Life Sciences, scientists from China Agricultural University systematically evaluate how generative AI is shifting crop breeding from selecting natural genetic variants to de novo molecular creation. The authors establish the "DESIGN" framework (Discover, Engineer, Simulate, Integrate, Generate, Navigate), linking molecular generation to field trials in a closed-loop learn-design-build-test cycle to accelerate Breeding 5.0.