The technological possibilities are expanding day by day. One of the biggest proof for this is the invention of AI. Like pharmaceutical regulatory affairs, Artificial intelligence in medical device regulatory affairs is also coming forward. AI is a never ending, ever expanding feature which can simplify things immensely. This presents us with an opportunity for expedited approval followed by introduction of medical devices into the market. Unlike pharmaceutical regulatory affairs, here AI is not only used in medical devices but interestingly AI can be a medical device.
Let’s explore how artificial intelligence influences the medical device regulatory affairs sector.
AI in Regulatory Submission of Medical Devices
Regulatory submissions are never easy and it always has a depth to it. Since AI has been introduced into the medical device regulatory field, the changes that it brings forward is impressive. Identification and compliance with the regulatory requirements specific to each region is a critical step in the product development lifecycle. Artificial intelligence can assist in this.
Apart from this it provides us with transparency, explainability, analyse the real world evidences from datasets which leads to effective decision making, recognize patterns from past submission data and can help with successful submissions, predict the lacking areas and what more can be done, automated testing, labelling, document preparation and storage… are the areas where AI play a significant role in medical device regulatory submission.
There are some major benefits of implementing AI in the medical device regulatory affairs. Let’s take a look at what they are.
Benefits of Medical Device Regulatory AI Solutions
Similar to that of pharmaceutical regulatory affairs the most common benefit is the minimisation in the time utilized. Some other benefits include:
- Predict the safety performance of the medical device with the help of big data structures
- Speedy submission and approval process
- Improved product quality, Less human effort and tracking
- Lower chances for error, error detection in medical device final assembly as well as manufacturing
- Improved accuracy and efficiency allows for earlier detection of diseases. As a result, can adapt more cost effective as well as less invasive treatment plans.
- Data analysis, data protection and patient safety
- Discover new patterns and safety signals among datasets (In pharmacovigilance)
- Device classification assistance as per the regulatory specifications of each region
- An increase in regulatory compliance rate
- Post market surveillance including possible early risk detection
- High quality service at any time of the day
- Streamlined regulatory operations and less exhaustive
Regulatory Automation in Medical Device
Regulatory process is an ongoing process until the product is no longer available for the consumers to use. To streamline this ongoing process, certain automation tools are available. This provides us with a chance to get better access to smart, reliable and quality services. With the introduction of these automation tools, more manual energy and time can be given to crucial tasks and can brainstorm for new concepts, ideas or even solutions.
Electronic Document Management System (EDMS), Regulatory Information Management (RIM) System, AI (Artificial Intelligence) Analytical Tools, Natural Language Processing (NLP) and Submission Publishing Tools are some of the regulatory automation tools used in the medical device regulatory area.
Also Read: AI Solutions For Pharmaceuticals
AI as a medical device (AIaMD)
AIaMD is a medical device that uses machine learning as a whole or partly to accomplish the medical purpose it is intended for. As per the study published by Alice Guo and Matte Morio in May 2024, there is no harmonized global standard or a body that specifically governs AI and ML in medical devices.
Since there is no harmonized pathway or standard for AIaMD, they must follow the existing medical device regulations like the GMLP, The EU AI Act, The action plan and change control plan of the FDA and medical device regulation of the country.
AI in Medical Devices & The Regulatory Body: Are they in sync?
As technology is expanding, advanced features can be introduced or even better it can lead to the development of novel medical devices into the market to satisfy patient needs. Due to this reason the global market is under continuous evolution. Therefore, it is important for the regulatory to know the ongoing market and stay abreast of all these. Since everything has its pros and cons, here also when coming to AI in medical devices there is no exception.
So, it is crucial for the regulatory body to take it into consideration and create a guideline or specific requirements for such medical devices to comply with. Regulatory authorities like the FDA have already created such documents and they are listed below.
- “FDA – Proposed Regulatory Framework for Modifications to Artificial Intelligence/Machine Learning (AI/ML)-Based Software as a Medical Device (SaMD) – Discussion Paper and Request for Feedback” : FDA has published this discussion paper in April 2019 which describes the potential approach to premarket review of AI/ML (Artificial intelligence and Machine Learning) driven software modifications.
- “Artificial Intelligence and Machine Learning Software as a Medical Device Action Plan”: FDA has published this action plan in January 2021.
- Good Machine Learning Practice for Medical Device Development: Guiding Principles: Published on October 2021
- In between there are other draft guidelines that were published. Guiding principles for predetermined change control plan for machine learning enabled medical devices and transparency for machine learning enabled medical devices were issued in October 2023 and June 2024 respectively.
- A final guidance was published in December 2024 regarding the Marketing Submission Recommendation for Predetermined Change Control Plan for Artificial Intelligence enabled device software functions.
Regulatory framework for AI
It is important to follow Good Machine Learning Practices (GMLP). It is a set of artificial intelligence and machine learning (AI/ML) best practices. The stakeholders had a strong interest in this concept knowing its significance. The GMLP allows for the safe, effective and high quality development of medical devices that use artificial intelligence and machine learning.
How a Medical Device AI Consultant Can Help?
A medical device AI consultant can be of help in many ways. It helps you to kick off and stay ahead in the game. Some examples on how it can aid are as follows:
- Can determine whether the particular device qualifies to be a medical device.
- Assist with the design of the device, documentation process, literature review.
- Helps with AI specific SOPs and quality management systems.
- Risk management solutions and documentation.
- Selection of apt AI tools depending on the type of device.
- Regulatory compliance and submission. Can get to know about any specific standards or documents to follow mandatorily specific to region, if any.
- Follow up post market entry.
Also Read: AI and ML in Drug Discovery
AI Tools For Regulatory Operations
Regulatory processes require time, patience, mandatory and requested documents and everything presented must be of quality and justifiable. This is not an easy process. To lessen this burden, there are lots of AI tools available. Choosing the right AI tool is the key. So down below are some things to consider while opting for AI tools for the regulatory operations to run smoothly.
Want to experience a streamlined regulatory journey with the help of AI? Artixio is here to assist you with regulatory AI consulting services. Choose the right AI tools, get access to specific AI solutions and much more with Artixio’s regulatory AI consulting services.
Conclusion
AI has undoubtedly become a helping hand in almost every sector. It is no exception in the medical device field as well. It can help in every aspect of the product journey, from its design to approval to post market surveillance. Incorporating AI must no longer be seen as an option but as a smart move that medtech companies must consider.
Getting a medical device approved and into the market is tough — anyone in the field knows that. And no, AI won’t magically make the entire process effortless. But it does take away some of the grind, like handling endless documents or spotting issues earlier than we could on our own. We’re also seeing the same shift in digital health regulatory. Apps, wearables, connected platforms — they’re changing the way doctors and patients talk to each other, sometimes in ways we didn’t expect. The point is, this change is already underway. The question is whether you just watch it happen or step in and be part of it.
