Given how baked-in AI and machine learning are becoming in the medtech space, it is of great importance that developers tapping into the technologies are transparent about how exactly these facilitators of convenience and cost-cutting are performing their duties, particularly in regard to sensitive matters such as patient data. Additionally, the onus is on SaaS vendors and the like to demystify the “black box” aspect of the rapidly advancing technology in play in their products. Ultimately, inherent comprehension of AI from buyers as well as proper labeling and marketing from sellers will make it a more accepted as well as viable medtech market mainstay.
Pear Therapeutics Chief Medical Officer and Head of Development Dr. Yuri Maricich, speaking at the recent AdvaMed MedTech Conference in Boston on a panel called “Artificial Intelligence in Medical Devices: Post Pandemic Implications,” said, “Typically, when we make a pure hardware or a pill, patients aren’t expecting to give their information back to the manufacturer. With connected devices, we’re asking them to give their information back to the manufacturer, so we have this almost sacred duty to protect that data if we’re going to maintain trust. If we violate that trust, it’s going to make it so much harder for all of us to actually bring technologies that are really effective.”
The issue of labeling is an admittedly tough nut to crack, though, according to industry experts. Some say that the FDA could afford an extra bit of leeway in its labeling policies to help AI developers better reach users where they actually are. Exclusively electronic labeling could be a suitable solution, as it automatically keeps up with updates and modifications and might be the best option for adaptation to a wide range of patient needs in the forms of different languages, text variations, or even descriptive video content.
