A group of scientists from Harvard University have observed and reconstructed the human brain at the resolution of the electron microscope, with all its cells, following all the connections between its neurons around a cubic millimeter of a tissue sample. They took 10 years and the data occupies 1.4 petabytes (1,400 terabytes). However, they are already planning a bigger project.

Artificial intelligence recently roiled the regulatory world, but the U.S. Congress has yet to dive into the task of legislating on the concept. Barrett Tenbarge, general counsel for Sen. Bill Cassidy (R-La.) told an audience here in the nation’s capital that while the Senate is considering several legislative proposals, the desire to avoid legislation that will create as many problems as it solves suggest that legislative development “is a long-term process.”

As the average cost of new drug R&D continues to skyrocket, the perception around using artificial intelligence (AI) as a tool to boost drug discovery is changing. “Developing new AI-based drugs is a difficult task, not only for Korea but also for countries with leading AI technology,” Hyeyun Jung, principal researcher of Korea Health Industry Development Institute’s Center for Health Industry Policy, told the audience at the Bio Korea meeting on May 9. “But there is a change in perception; [namely that] applying AI to new drug development is not an option but a necessity.”

Profound Medical Corp. received U.S. FDA 510(k) clearance for its second transurethral ultrasound ablation (TULSA) module using artificial intelligence. When used with Profound’s TULSA-Pro system, the Contouring assistant helps physicians more quickly and accurately segment prostate imaging and design treatments.

As the average cost of new drug R&D continues to skyrocket, the perception around using artificial intelligence (AI) as a tool to boost drug discovery is changing. “Developing new AI-based drugs is a difficult task, not only for Korea but also for countries with leading AI technology,” Hyeyun Jung, principal researcher of Korea Health Industry Development Institute’s Center for Health Industry Policy, told the audience at the Bio Korea meeting on May 9. “But there is a change in perception; [namely that] applying AI to new drug development is not an option but a necessity.”

Avicenna Biosciences Inc. has introduced an extension to its machine learning (ML) technology platform to enhance medicinal chemistry and expedite clinical-stage drug discovery.

The U.K. Medicines and Health Care Products Regulatory Agency (MHRA) is among the regulators across the globe that are scrambling to keep pace with artificial intelligence (AI) in medical devices, releasing an April 30, 2024, paper on its own approach. One of the key considerations in this paper is that MHRA expects to up-classify some AI-enabled device software functions in its ongoing regulatory revamp, a prediction that suggests a more stringent premarket path for these products in the years ahead.

Recent advances in artificial intelligence (AI) have generated a tsunami of popular dystopian musings, but the U.S. Patent and Trademark Office (PTO) has its own concerns about AI’s impact on intellectual property. PTO recently announced that it is looking for feedback on the use of AI to produce what litigants might spuriously claim is prior art, a concern that must be addressed if the patent system is to avoid crashing under the weight of an unmanageable volume of AI-generated clutter.

In what represents its first patenting, PBSF Inc. filed for protection of brain monitoring and neuroprotection strategies for infants at high risk on a large scale.