If finalized, EPA’s proposals are estimated to cut EtO emissions to the air from commercial sterilization facilities by 80% per year and apply more protective standards to control those emissions under the law. But MedTech advocates are concerned that the EPA is overlooking the controls already in place and a lack of alternatives that could lead to patient risks.
Data integrity issues have plagued the pharma industry since its inception. Blockchain, with its potential to assist in processes from product serialization to data flow tracking, could be the best solution yet.
By deploying connected intelligence systems at a global scale, teams can navigate go-to-market challenges by increasing the transparency and predictability of the complex and divergent global product registration processes.
Digital transformation is especially important to medical device manufacturers because they must have good quality data, and especially tracking metrics, to track complaints and device performance to comply with regulatory requirements. And these requirements are just getting stricter.
Anyone can read the regulation. The challenge is in how to apply it to your company’s structure and product line.
Although medical device manufacturers have more time to prepare due to the delayed EU MDR deadline, this shouldn’t distract from the extensive documentation they must compile in the meantime to prove their devices are compliant.
As the proliferation of connected and complex medical devices grows, healthcare providers are more susceptible to cyberattacks.
Make sure your 510(k) submissions pass with flying colors. Explore the latest regulations impacting bacterial endotoxin testing.
The latest regulations for human and veterinary medicinal products, as well as medical devices, include the mandate to set up databases with detailed information about available products. These databases must be realized and implemented in the near future, and require a concerted effort now if tangible real-world benefits are to follow.
Artificial intelligence and machine learning technologies have significant potential, but regulatory hurdles may stand in their way.