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).

The next wave of drug discovery is being enabled by powerful computers dining on complex algorithms to uncover potential new scientific approaches for the development of innovative therapeutics. This fact has not been lost on venture capital firms specializing in the health care space that are beginning to support emerging biopharma companies that are using artificial intelligence (AI) and machine learning (ML) to supercharge their drug discovery and development activities.

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.

Winter is coming to the artificial intelligence industry. While it's springtime for investment and technological advancement, gray skies hover over the talent pool.

The hype surrounding artificial intelligence (AI) can make it sound like the technology has all the answers. But from a scientific perspective, one of the technology's biggest strengths is that it can ask better questions.

Information technology has been promising for decades, largely since the advent of electronic medical records, 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 and machine learning, 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.

The U.S. Supreme Court's decision in Alice earlier this decade has closed the door on many drug and device patents involving artificial intelligence, as such claims are likely to be dismissed as abstract ideas, which means they can't get through what's become the patent eligibility rabbit hole of Section 101 of the Patent Act.

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.

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.

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.