The U.S. FDA has granted breakthrough device designation to Potrero Medical Inc. for its AKI Predict machine learning algorithm for the advanced prediction of acute kidney injury (AKI) associated with intra-abdominal hypertension (IAH) in intensive care patients recovering from cardiac surgery.
International research project Multicentre Epilepsy Lesion Detection (MELD), led by University College London, has developed artificial intelligence software that can identify minute brain anomalies that lead to epilepsy seizures. These anomalies, known as focal cortical dysplasia, can often be treated with surgery but are difficult to visualize on an MRI.
Cognetivity Neurosciences Ltd. is making progress in promoting its cognitive assessment tool as the brain health equivalent of a blood pressure check, following feedback from clinicians indicating the test could have broad applicability.
Cleerly Inc. sees a bright future ahead after boosting its fundraising to date nearly five-fold with a $192 million series C. The new infusion brought the total invested in the company to $248 million, a solid endorsement of a company that hopes to transform cardiology with precision-based diagnostics that move away from indirect indicators to accurate measurements.
Kranus Health GmbH has raised $6.5 million in series A funding to ramp commercialization of its digital therapy for treating erectile dysfunction (ED). Eleven European investors participated in this fundraising. The round was led by early-stage health care venture capitalists Karista SAS, while Peak Pride Management GmbH also joined the funding round.
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.
Artificial intelligence (AI) and machine learning (ML) present regulators and payers alike with some interesting dilemmas, but that statement can be applied to patent offices and inventors as well. In this fifth installment in a series on AI in radiology, we’ll examine the hazards of acquiring and sustaining intellectual property protection for these algorithms, a much more complicated and complex undertaking than many developers might appreciate.
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.
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.
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.
