The U.S. FDA may be the most advanced regulatory agency when it comes to artificial intelligence (AI) and machine learning (ML), but developers of these products still have little in the way of FDA guidance to work with in many instances. Cassie Scherer of Dublin-based Medtronic plc, told attendees at this year’s Food and Drug Law Institute annual conference that they should have a product change control protocol ready to go despite the absence of FDA guidance on the subject, an effort that will increase time to market but pay eventually big dividends.

Ibex Medical Analytics Ltd. extended the reach of its artificial intelligence (AI) powered pathology system, adding gastric cancer to existing CE mark approvals in prostate and breast cancer.

Diabeloop SA has just closed a series C funding round, securing $73 million to ramp global expansion for its DBL1 integrated smart system for patients with type 1 diabetes. “This will allow us to boost commercial roll-out and continue pursuing our growth strategy into Europe, the U.S. and Asia,” Erik Huneker, CEO of Diabeloop, told BioWorld.

Developers of artificial intelligence (AI) and machine learning (ML) algorithms in medical radiology tend to think of regulatory approval as the primary hurdle to market, but there is also the question of how to pay for the use of these products. Public and private payers obviously hold the purse strings, but appealing to payers is still not always as straightforward proposition as some would like, reinforcing the notion that coverage and reimbursement still combine to serve as one of the highest hurdles to market for AI and ML.

Artificial intelligence (AI) and machine learning (ML) algorithms for use in medical radiology have made tremendous inroads into clinical practice, but one of the key stakeholder groups, physicians, aren’t always persuaded of the benefits of these software products. In this second installment of a six-part series, BioWorld asked Bibb Allen, Jr., chief medical officer for the Data Science Institute of the American College of Radiology, what physicians want, and what physicians see as a trend toward me-too AI.

Tel Aviv-based startup Scopio Labs Ltd. has received U.S. FDA 510(k) clearance for its artificial intelligence (AI) powered cell morphology platform, X100HT. The laboratory device is designed to locate and display images of white cells, red cells and platelets acquired from fixed and stained peripheral blood smears. Analysis of the images is then provided using AI technology.

Stratipath AB gained CE-IVD mark for its artificial intelligence (AI)-based software for prognostic risk stratification of breast cancers, clearing the path for introduction of the solution in the EU. Stratipath Breast analyzes digital histopathology whole slide images generated from surgically resected breast cancer tissue to identify patients with increased risk of disease progression. The system provides clearer guidance on the best treatment path for the 50% of women whose breast cancer is categorized as intermediate risk.

Medi-Globe GmbH, in conjunction with the Institut Hospitalo-Universitaire (IHU) in Strasbourg, France, is developing new artificial intelligence (AI) software for the detection of pancreatic disease. The Rohrdorf Germany-based company just completed a first-in-human trial of this AI tool during an endoscopic ultrasound examination performed at the Institute of Image-Guided Surgery at IHU.

Retispec Inc. and the Toronto Memory Program launched a community screening program for Alzheimer’s disease (AD) funded by the Davos Alzheimer’s Collaborative (DAC). The program will provide two points of entry for screening—optometry clinics and the Alzheimer Society of Toronto. The project is one of 12 early detection efforts worldwide that received a total of $4.5 million in funding this week from DAC.