Unlike a biocompatibility study that can be scheduled for a specific quarter, cybersecurity cannot be treated as a one-time milestone. It must be an iterative process integrated throughout the entire product lifecycle, from initial design and software development to post-market surveillance.
Retrofitting cybersecurity into a medical device near submission is a common, catastrophic error. The FDA requires security to be designed-in from the start. "Bolting it on" later leads to significant delays and costs, much like trying to add rebar to an already-poured foundation.
The primary lens for medical device cybersecurity should be patient safety, not data protection. A hacked device can directly harm a patient, making security as fundamental as sterility. This reframing changes the entire approach from a compliance checklist to a core design principle.
MedTech companies mistakenly assign product cybersecurity to their IT teams, whose focus is data protection. Product security is about patient safety and should be owned by Quality Assurance, as all documentation must integrate into the Quality Management System (QMS) like other design files.
While AI cybersecurity is a concern, many MedTech innovators overlook a more fundamental danger: the AI model itself being flawed. An AI making a wrong recommendation, like a therapy app encouraging suicide, can have dire consequences without any malicious external actor involved.
A MedTech company was forced to disable key features to gain FDA clearance because a microcontroller selected two years earlier lacked necessary security capabilities. This shows how seemingly minor, early hardware decisions can have irreversible and costly consequences on the final product's functionality.