• Microsoft, Ginkgo Collaborate to Demonstrate Lab-in-the-Loop Biology

    Bio-IT World | Earlier this month at Microsoft Build 2026, Microsoft announced general availability of Microsoft Discovery, a platform designed to support the iterative testing cycles inherent in research and discovery workflows by helping build and govern agentic AI workflows across scientific and engineering disciplines, supporting the iterative loops, evidence preservation, and tool coordination that define scientific work.

    Jun 15, 2026

  • From Automation to Autonomy: How Agentic AI Is Redefining Biopharma’s Digital Workforce

    Bio-IT World | Biopharma’s relationship with automation has historically been pragmatic and incremental. Robotic process automation, rules‑based workflows, and task‑specific machine‑learning models have been widely deployed to reduce manual effort and accelerate well‑defined tasks. These approaches delivered value, but they remained fundamentally limited: each tool addressed a narrow slice of work, often creating additional handoffs between systems and teams.

    Jun 12, 2026

  • Navigating the Perilous Journey from Lab to Market

    Bio-IT World | The translation of promising lab ideas into commercial impact is fraught with multiple valleys of death, beginning with the technical, funding, and people challenges of getting medical interventions out of academia and into clinical trials in the first place.

    Jun 10, 2026

  • As AI Reshapes Drug Discovery the Lab Remains the Bottleneck

    Bio-IT World | At a plenary session at the Bio-IT World Conference & Expo last month, Jeremy Jenkins, a computational drug discovery leader at Novartis, delivered a frank and wide-ranging assessment of where artificial intelligence is genuinely accelerating pharmaceutical R&D — and where it keeps running into the same old wall: biology.

    Jun 9, 2026

  • Federation Plus Fine Tuning: The Push for Federated Learning Models Continues

    Bio-IT World | Federated learning is changing the rules in drug discovery, argued a group of speakers at last month’s Bio-IT World Conference & Expo. The opportunities are robust, but success depends on establishing trust and fine-tuning models for individual applications.

    Jun 4, 2026