
Pharma Regulatory AI Draws Ninety-Five Million Dollars
A massive influx of capital into clinical trial automation signals that the next high-value AI frontier is boring paperwork.
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A massive influx of capital into clinical trial automation signals that the next high-value AI frontier is boring paperwork.

Static bone density scans miss how a patient’s body changes over time, but a new deep learning model proves that tracking those physical trajectories can prevent missed fracture risks.

A new UK regulatory initiative is putting AI to the test to solve the pharmaceutical industry’s most expensive problem: high failure rates.

Doctors write down clues about their patients’ loneliness, but those warnings usually sit buried in unstructured text where no one can find them.

Getting a prescription for the world’s most sought-after weight-loss drugs has devolved into a frictionless, five-minute checkout process.

Training diagnostic AI no longer requires massive, expensive libraries of real patient photos.

A decade of silent suffering for endometriosis patients might finally be cut short by a shift toward non-invasive diagnostics.
A new analysis of wearable data shows that tracking how we move during sleep can flag Parkinson’s risk a decade before clinical symptoms appear.

The federal government is loosening its grip on low-risk digital health tools, but developers who mismanage their marketing claims will still face regulatory crackdowns.

A new machine learning model can pinpoint which ankle fracture patients are highly likely to develop surgical infections, but its tendency to miss the majority of at-risk cases makes it a dangerous tool if used as a standalone safety net.