PERTH, Australia – Wellington, New Zealand-headquartered Volpara Health Technologies Ltd. has acquired Boston-based CRA Health LLC for $18 million up front and an additional $4 million to be paid over the next 18 months in earnouts. Volpara’s digital health solutions use imaging and artificial intelligence (AI) for early detection of breast cancer. The company’s clinical functions for screening clinics provide feedback on breast density, compression, dose, and quality, while its enterprise-wide practice software management helps with productivity, compliance, reimbursement and patient tracking.
Regulatory snapshots, including global submissions and approvals, clinical trial approvals and other regulatory decisions and designations: B-Secur, Claronav Kolahi, RapidAI, Precision Biomonitoring, Precision Spine.
Biosig Technologies Inc. and the Mayo Foundation for Medical Education and Research are jointly developing next-generation artificial intelligence (AI)-powered software for Biosig’s Pure EP electrocardiograph system. The Pure EP system acquires, measures, calculates and stores electrocardiographic and intracardiac signals for patients during electrophysiology procedures. The collaboration aims to expand the captured signals and combine them with other data sources to provide more actionable information.
Regulatory snapshots, including global submissions and approvals, clinical trial approvals and other regulatory decisions and designations: Clew, Pulse Biosciences.
BERLIN – The German government has just made $3.6 billion available to the Future of Hospitals Act (Krankenhauszukunftsgesetz, KHZG), through the liquidity reserve of the health fund in order to support public hospitals with digital transformation. Besides this government cash injection, an additional $1.6 billion will be made available through co-funding by the German federal states, the 16 Länder. In total, German hospitals will get a $5.2 billion funding to boost digitization.
The expansions of coverage of telehealth associated with the COVID-19 pandemic will persist after the pandemic is over, even if the post-pandemic utilization does not match the current rates and types of utilization. However, speakers on a recent webinar hosted by Moses & Singer LLP of New York said that state medical licensure practices after the pandemic could be a help or a hindrance to more widespread use of telehealth, an issue stakeholders will want to track as 2021 unwinds.
LONDON – The U.K. National Institute for Health and Care Excellence (NICE) has published new advice on how and when artificial intelligence (AI) could be applied to the interpretation of mammograms and chest computer tomography images, in a move that is intended to set the ground rules for the uptake of these technologies. In population breast screening, NICE looked at how five AI systems could be used to pick out mammography images that need further assessment, supporting qualified radiologists in their interpretation.
TORONTO – Startup CEOs may sometimes be forgiven a little exuberance on learning their technology has received the high sign from regulatory officials. So it was when the head of Monitio Intelligence Inc. Ben Su sifted through his email at his office in Coburg Ontario and saw the Health Canada logo at the top of the letter. “I was actually jumping up and down when I received that authorization letter. I was very excited,” Su said. Since then Su has been overseeing installation of an automated COVID-19 screening system.
Regulatory snapshots, including global submissions and approvals, clinical trial approvals and other regulatory decisions and designations: Advanced Medtech, DNA Genotekm, Global Instrumentation, Perspectum.
Using Rhythm AI Ltd.'s stochastic trajectory analysis of ranked signals (STAR) mapping system with pulmonary vein isolation terminated and eliminated recurrence of persistent atrial fibrillation (AF) at much higher rates than other ablation procedures in a study published in the Journal of Cardiovascular Electrophysiology. The artificial intelligence-driven STAR mapping process collects and analyzes thousands of heart signals to precisely identify the areas of the heart responsible for the errant electrical signals causing atrial fibrillation, enabling more thorough and accurate ablation.