Infervision Medical Technology Co. Ltd. received approval from China’s NMPA for its radiological computer-assisted triage and notification software device Inferread CT Stroke. This is the first class III approval that the firm obtained in the cerebro-cardiovascular field. Class III approvals are for high-risk medical devices.
Medtronic plc has entered a strategic collaboration with Cathworks Ltd. to expand the reach of Cathworks’ artificial intelligence (AI) guidance system for coronary artery disease management. Medtronic will invest up to $75 million and immediately begin co-promotion of the Ffrangio system on the U.S., European and Japanese market. As part of a separate agreement, Dublin-headquartered Medtronic will have the option to acquire Cathworks once certain undisclosed milestones are met.
Clinical analytics company Medial Earlysign Ltd. is expanding an existing partnership with Roche Holding AG to commercialize an artificial intelligence (AI) solution for the early detection of lung cancer. The companies originally signed an agreement in September to develop a personalized health solution for early detection of gastric cancer. The goal of the new collaboration is to develop Earlysign’s Lungflag software, which uses machine learning to identify patients at risk of developing lung cancer.
A French public-private consortium of seven med-tech companies, research institutes and specialist cancer hospitals is launching a new project to standardize and improve access to health care data for cancer research. Paris-based Arkhn SAS and Owkin SAS joined forces with INRIA, the French national institute for research in digital science and technology, to launch Oncolab.
Envision Technologies BV’s latest artificial intelligence (AI)-powered smart glasses for the blind and visually impaired are designed to help with reading, scanning faces and navigating everyday tasks. This visual assistant was introduced at California State University Northridge (CSUN) 2022 Assistive Technology Conference. Envision has updated its AI-based platform and ecosystem with improved optical character recognition (OCR) and better text recognition with contextual intelligence.
Regulatory harmonization of artificial intelligence (AI) and machine learning (ML) is high on the checklist for companies that want to develop these products, but legislatures and regulatory agencies across the globe seem less interested. Koen Cobbaert, senior manager for quality standards and regulation with Royal Philips NV, told BioWorld that there is a race on to be the first market with a full-fledged set of regulations, a fact of life that does little to advance the cause of harmonization.
The FDA has rejected Artrya Ltd.’s 510(k) application for its Salix coronary anatomy (SCA) software that analyzes heart computed tomography scans via artificial intelligence (AI) to better diagnose coronary artery disease. “The FDA has advised that the Artrya Salix product is not equivalent to the predicate device,” Artrya CEO John Barrington told BioWorld.
Los Angeles-based cancer diagnostics company Nonagen Bioscience Corp. obtained CE marking for its Oncuria immunoassay for bladder cancer. The multiplex urine test is designed to detect the concentration of 10 proteins that are associated with bladder cancer in urine samples. Clinical studies found the test has a 93% sensitivity and 93% specificity for detecting bladder cancer. The test is also designed to predict whether people are more likely to respond to bacillus Calmette-Guérin (BCG) therapy, a first-line treatment for bladder cancer.
The U.S. FDA is among the regulators that are taking account of the views of patients in medical device development and regulation, but artificial intelligence (AI) and machine learning (ML) are terra incognita for many, if not most patients. Rebekah Angove, vice president for patient experience and program evaluation at the Patient Insight Institute, told BioWorld that while some patients clearly want to know more about AI and ML, it is also clear that more than a certain amount of detail is more of a distraction than a help for most patients.
Artificial intelligence (AI) and machine learning (ML) are all the rage in 2022 when it comes to medical radiology, but regulators across the globe are struggling to devise regulatory frameworks that ensure safety and efficacy without strangling innovation. There are a number of other stakeholders in this sphere of med tech, however, each with their own considerations. In this six-part series, BioWorld will examine these considerations in an effort to characterize the working environment for AI and ML as it exists now, and what that environment might look like in the years ahead.
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