History has shown that regulatory missteps can derail even the most promising medical devices. One example is the Dalkon Shield, an intrauterine device (IUD) that was introduced in the 1970s without sufficient safety testing. The device led to severe infections, infertility, and even deaths, ultimately resulting in lawsuits and stricter FDA regulations under the 1976 Medical Device Amendments. This case highlights why compliance with regulatory requirements must be an integral part of project management.
Modern regulations, such as Good Manufacturing Practices (GMP), ISO 13485 and ISO 14971 standards, ensure that medical devices are developed under controlled conditions. However, project teams must remain vigilant - even small deviations from regulatory protocols can lead to market rejection or recalls.
While the 510(k) premarket notification process allows for faster approvals by demonstrating substantial equivalence to existing devices, poor regulatory planning can result in denied submissions or additional testing requirements. Hence, regulatory teams play a crucial role in identifying potential risks and ensuring compliance throughout the development cycle.
In your opinion, what is the most common regulatory pitfall in medical device development today? Is it insufficient clinical data, inadequate risk management, or unclear regulatory pathways?
One of the most common regulatory pitfalls in medical device development today is underestimating regulatory requirements from the start[1]. This often leads to project delays, increased costs, and even market rejection. Insufficient clinical data is another significant issue, as it can result in denied submissions or the need for additional testing[2]. To avoid these pitfalls, it's crucial for project teams to engage regulatory experts early in the development process and maintain rigorous documentation and compliance with standards like GMP, ISO 13485, and ISO 14971[1]. How do you think early and continuous regulatory engagement can improve the chances of a successful medical device launch?
References
[1] 10 Common Mistakes to Avoid in Medical Device Development
@ms3548 Underestimating regulatory requirements is indeed a common pitfall that does not get enough attention in my view. Implementing steps for early and continuous regulatory engagement can ensure a company can properly plan their pathway for receiving approval for their device. The pathway to approval depends greatly on the classification of the device. Early input from individuals well-versed in the regulatory field of medical devices can ensure a product proceeds through the correct pathway for approval. For example, identifying a medical device within the wrong category could be detrimental to the approval process for a medical device. Likewise, the lack of a sufficient 510K or PMA could result in financial implications and time lost. Continuous regulatory engagement can also ensure that a product is compliant at all stages of development. For new devices using more modern technology, like AI, would most definitely require continuous regulatory engagement. Early and proactive engagement would be critical to projects involving AI as it is most probable that in the near future, many new regulations will be made, and older regulations may be adjusted. Understanding this early, and maintaining regulatory engagement would be critical for the success of the project, regardless of the scope of the project.
I agree with the previous claims of underestimating regulatory requirements from the start. To add to that, picking the wrong classification of your medical creation will certainly create problems. Your potential product will fall under a single or a combination of the three regulation paths of CDRH (medical device), CDER(Drug), and CBER(Biologic). The project management should acknowledge and understand the different requirements each path entails before they decide to submit anything. Medical creations that fall under just a single path out of these three have it the easiest compared to combination devices that have more than one path/identity. The "primary mode of action" is the single mode of action that identifies the main function of the medical product and it identifies which path the combination product should be placed in. The people working on the project can possible misunderstand the "primary mode of action" of their device which can totally throw off their schedule and lead to possible development failure. As Dr. Simon said in his lecture, say a team is put together for a project that is comprised of personnel that are specialized in medical devices. Then their combination product is placed in CDER by the FDA which can very likely end their product development since they do not have any people in the team that are more specialized in Drugs.
I'd also agree that inadequate risk management is the most common regulatory pitfall in medical device development. Classification of the device can be a difficulty in the project management process as mentioned above. I'd like to add that submitting an RFD (request for designation) can cause complications in medical device development and slow a project's timeline. It is highly recommended to manually choose a class for your medical device rather than submitting an RFD for these reasons.
One regulatory challenge in developing medical technologies with AI is exploring real-world data in clinical practice. As technology is evolving quickly, regulatory agencies have an urgency to be proactive with guiding principles to promote safety and efficacy in the development of AI medical devices. Hence, strict oversight is necessary simultaneously to provide patient care and endorse the “the human-in-the-loop” (HITL). This principle ensures the development of AI on medical devices where humans evaluate machine learning models to provide final decisions based on training data, model performance, feedback, and bias monitoring. In addition, in 2023, the FDA published the Draft: Use of Real-World Evidence to Support Regulatory Decision-Making for Medical Devices. The principle behind this initiative is to provide guidelines clarifying how to evaluate if real-world data (RWD) is of “sufficient quality” and is reliable for researchers and developers to reduce bias. Therefore, the future of Artificial Intelligence in Medical devices promises to be sufficient to improve patient care positively, providing innovative tools to access a prompt diagnosis. The key issue in this development is data validation time in such systems and how evolving algorithms will be trusted for patient care.
Effective medical device project management requires a thorough understanding of regulatory requirements to avoid compliance issues. Teams should stay updated on FDA, ISO, and other relevant regulations throughout the development lifecycle. Proactive risk management, proper documentation, and early engagement with regulatory bodies help mitigate potential delays. Ensuring clear communication between engineering, quality assurance, and regulatory teams is essential for a smooth approval process.
