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Stryker Cyberattack Delays Patient Surgeries

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A cyberattack on medical device manufacturer Stryker has led to delays in certain patient surgeries, according to a report.

The disruption affected the company’s ability to deliver personalized medical inventory, forcing some procedures to be rescheduled. The issue stemmed from a broader system outage that impacted operations including order processing, manufacturing and logistics.

An Iran-linked hacking group claimed responsibility for the attack, which caused widespread business disruption. Stryker later stated that the incident had been contained and emphasized that no patient-care systems or connected medical devices were directly affected.

However, the delays highlight how cyber incidents can indirectly impact healthcare delivery, even when core medical systems remain operational.

Drugmakers Turn to AI to Speed Trials and Submissions

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Pharmaceutical companies are increasingly using artificial intelligence to accelerate clinical trials and regulatory submissions, even as AI has yet to deliver major breakthroughs in discovering new drugs. Industry executives say the technology is already saving weeks by automating participant recruitment, site selection, and the preparation of vast regulatory documentation.

Executives from major drugmakers including Eli Lilly, AstraZeneca, Roche, and Pfizer said at the JP Morgan Healthcare Conference that AI tools are helping manage thousands of pages of clinical, safety, and manufacturing records required by regulators worldwide.

Drug development can take more than a decade and cost around $2 billion. Companies are betting that AI can improve efficiency and success rates by handling what executives call the “messy middle” of development. Consultancy McKinsey estimates that autonomous, or agentic, AI could lift clinical development productivity by up to 45% over the next five years.

Israeli drugmaker Teva Pharmaceutical Industries said it is using AI to streamline processes so researchers can focus on bringing new medicines to market. Meanwhile, Novartis used AI to cut site selection for a large cardiovascular trial from weeks to hours, helping it hit enrollment targets with minimal overshoot.

Other companies are also reporting tangible savings. GSK said digital and AI tools helped reduce late-stage trial costs by millions of pounds, while Denmark’s Genmab plans to deploy AI agents to automate post-trial analysis and reporting.

While investors are still waiting for the first fully AI-designed blockbuster drug, executives say the technology is already reshaping how trials are run and how data is submitted. Amgen’s research chief said many AI-designed molecules are already moving through pipelines, suggesting the biggest impact may still lie ahead.

Bristol Myers Partners With Microsoft for AI-Driven Lung Cancer Detection

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Bristol Myers Squibb has signed a partnership with Microsoft to use artificial intelligence-powered radiology tools to speed up the early detection of lung cancer, the companies said on Tuesday.

Under the agreement, Bristol Myers will deploy U.S. Food and Drug Administration-cleared radiology AI algorithms through Microsoft’s Precision Imaging Network. The platform analyzes X-ray and CT scan images to help clinicians identify lung disease and is already used by hospitals across the United States.

The companies said the AI tools could help doctors detect hard-to-spot lung nodules and identify patients at earlier stages of disease, when treatment options are more effective. A key objective of the collaboration is to expand access to early lung cancer detection in medically underserved areas, including rural hospitals and community clinics.

Alexandra Goncalves, vice president and head of digital health at Bristol Myers Squibb, said the partnership combines Microsoft’s scalable imaging technology with Bristol Myers’ oncology expertise to create an AI-enabled workflow that supports faster and more accurate diagnosis of non-small cell lung cancer and guides patients toward appropriate care pathways.

Pharmaceutical companies are increasingly adopting AI to improve efficiency across research, development, and clinical workflows. The collaboration reflects a broader industry push to apply AI not only to drug discovery but also to diagnostics and patient care, particularly in oncology.