Tokyo-based Terumo Corp. already had a formal limited partner relationship with one U.S. venture firm, early medical device-focused, Mountain View, Calif.-based Emergent Medical Partners (EMP) that dates to 2013. Now it has added investment in two more venture firms, Santa Clara, Calif.-based Strategic Healthcare Investment Partners and Boston-based Catalyst Health Ventures.

In retrospect, it seems inevitable that an algorithm would be appointed to a board of directors. Hong Kong-based Deep Knowledge Ventures named Vital (an acronym for Validating Investment Tool for Advancing Life Sciences) to its board five years ago and credits it with making better decisions than its fellow members, humans all.

Concussion and traumatic brain injury (TBI) are serious public health problems, but they can be tricky to diagnose, with symptoms sometimes not presenting for days or weeks following a head injury. Abnormal eye movement can indicate a TBI, but traditional "follow my finger" screenings won't pick up more subtle changes in vision. Artificial intelligence (AI) could improve diagnosis by measuring deficits in certain eye movements that occur with a TBI. In a study published online July 25, 2019, in the journal Concussion, Bethesda, Md.-based Righteye Inc.'s FDA eye-tracking technology not only identified but scaled the severity of TBIs by measuring horizontal and vertical saccades, rapid eye movements between fixed points.

Artificial intelligence (AI) has helped the med-tech industry in numerous ways. From genomics, to screening, to diagnostics, AI has made things easier for clinicians.

And that has caught the eye of investors. According to Mercom Capital Group LLC, as a whole, digital health venture capital funding in the second quarter 2019 jumped from the previous quarter ($3.1 billion raised in 169 deals vs. $2 billion raised in 149 deals).

Information technology (IT) has been promising for decades, largely since the advent of electronic medical records (EMR), to improve and streamline health care as it has multiplied productivity in countless other industries. In addition to the long-standing problems with EMRs, more recently there have been early disappointments with the latest iteration of IT focused on artificial intelligence (AI) and machine learning (ML), as big players like IBM Watson and Google have tended to over-promise and under-deliver with algorithms that are poorly matched to the data or the patient need.

While regulatory science can lag behind technology advances, the FDA has for the past few years been exploring ways to harness the potential of artificial intelligence (AI) to streamline drug development and the approval process. A nexus for its efforts is the Information Exchange and Data Transformation (INFORMED) initiative anchored in the agency's Oncology Center of Excellence (OCE). At its inception in 2016, INFORMED was designed to tap into the power of big data and advanced analytics to improve disease outcomes.

BEIJING – With home-grown artificial intelligence (AI) medical devices under priority review, mainland China is quickly putting together a regulatory framework to more rapidly tap into the power of AI to develop devices and drugs.

PERTH, Australia – It's likely that Australia will not draft separate guidance or regulations for software applications that use artificial intelligence or machine learning (AI/ML) for drug development or medical devices. Instead, the Therapeutic Goods Administration (TGA) will classify AI and ML under software as a medical device (SaMD) when it is intended for diagnosis, prevention, monitoring or treatment or alleviation of disease.

NEW DELHI – Artificial intelligence (AI) is increasingly gaining a foothold in India's health care landscape, with investors pouring money into the new technology, companies developing products and regulators looking to come up with much-needed rules. India's Ministry of Health has reached out to the public for consultation on its national digital health blueprint that seeks to propel digital health care, including the use of AI in the biotech and medical technology sectors.

The FDA's regulation of artificial intelligence (AI) is divided by product center for reasons that are obvious, but precisely what that regulation will look like is anything but. As the FDA's Center for Devices and Radiological Health (CDRH) goes through the comment period for its discussion draft for AI, other nations are starting their own efforts in this space. The American agency's efforts may foreshadow the approaches employed in other nations.