In this article, the authors discuss new updates from the UK’s Medicines and Healthcare products Regulatory Agency on how software and artificial intelligence medical devices will be regulated in the United Kingdom after Brexit. Read and learn more!
"The potential to use artificial intelligence methods increasingly for the analysis of the increasing amounts of pharmacovigilance data is well understood and many companies are moving (or planning to move) there, and we can predict that routine tasks in pharmacovigilance will in the future be increasingly automated. It will be crucial, however, for regulatory authorities to very clearly provide a position about the use of AI as well as the acceptable level of quality from AI applications. But in parallel with the shaping of those definitions, given the massive increase in their AE case workloads that most companies are currently experiencing, the industry will out of necessity proceed swiftly with the adoption of AI and cloud technologies to reduce their costs and increase their efficiencies. "Like other industries, the pharmaceutical business and in particular the pharmacovigilance field will see a massive change in their processes in the near future, away from tedious, repetitive manual tasks towards a better utilization of scarce resources, in particular medical and scientific knowledge, for value-adding tasks. It is imperative for all stakeholders – industry, service providers and regulators – to provide an environment in which such a transformation can take place without ever compromising public health or the safety of the individual patient, and ideally providing additional benefit for patients." A quote from Addressing the Data [...]
Are Data Divers and Miners Going to Lead Innovation? The big tech companies are into it. Apple, IBM and Google. Roche is into it. Medtronic, as well. Artificial intelligence has been a big part of innovation in the healthcare space for several years, and its impact is only going to get bigger. "Artificial intelligence-based healthcare technologies have contributed to improved drug discoveries, tumor identification, diagnosis, risk assessments, electronic health records (EHR), and mental health tools, among others," writes Blank Rome attorney Brian Higgins in his Artificial Intelligence and the Law Blog (it's excellent, by the way). [1] Daniel Faggella of TechEmergence.com writes that machine learning healthcare applications are getting a lot of attention in the press and from the investment community. He adds to the list of machine learning's impact things like treatment queries and suggestions, and even robotic surgery. But optimism for AI's application to drug discovery seems greater than that inspired by other healthcare sectors. One reason for that, Faggella writes, is that compared to other segments where various laws and stakeholder incentives may not align, "drug discovery stands out as a relatively straightforward economic value for machine learning healthcare application creators." He adds that this application also involves "one relatively clear customer who happens to generally have deep pockets: drug companies." [2] Also writing for TechEmergence.com, Kumba Sennaa says [...]
