PERTH, Australia – There is pervasive use of artificial intelligence and machine learning (AI/ML) across the health care industry in Australia, and excitement is building on the opportunities it offers to technologies and ultimately to patients, Ausbiotech CEO Lorraine Chiroiu told BioWorld.

Just as artificial intelligence (AI) becomes an ever-more common part of drug discovery, its potential role in clinical trials is slowly becoming more visible, too. Efforts to improve trial recruitment, efficiency and decision-making are underway at companies of all sizes as organizations look to better the oft-daunting odds of clinical success, industry executives told BioWorld.

By streamlining processes, cutting costs and improving data quality, artificial intelligence (AI) and machine learning can reduce clinical trial spend and speed time to market. The technology is showing up in a number of applications, from guiding recruitment to developing biomarkers to determine who will respond to certain treatments and driving cost efficiencies.

The U.S. Patent and Trademark Office (PTO) is seeking feedback on artificial intelligence (AI), posing questions on whether the regulations or even the statute will have to be amended to allow the agency to issue patents for items invented in part or in whole by AI.

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.

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.