Wearable Medical Devices and SaMD solutions are revolutionizing patient care across the world. With its power of remote and continuous patient monitoring, they have been helping healthcare providers, payers, CROs, Life Science organizations, and patient ecosystems.
With each class of wearable medical devices and its increasing risks, Medical Device companies must adhere to different regulations set by the regulatory body FDA. The basic purpose of these regulations is to ensure that medical devices are safe for patients.
But compliance and regulatory requirements for each class of devices are different. Wearable Medical Device companies have to set up Regulatory teams to create documents that need to be submitted to the FDA.
Challenges in generating and publishing FDA compliance documents:
Since medical devices directly affect the patient’s health and store critical information, there are many prelaunch and post-launch compliances that FDA has introduced. Due to the lengthy procedures and knowledge-intensive approach, FDA approval for medical devices is a big challenge, and many medical device companies get stuck in regulatory limbo due to the following challenges:
Challenges faced by regulatory teams:
- Identifying and classifying the device
- Understanding and identifying device regulations and compliance requirements
- Putting together information and data for publishing
- Non-productive hours of Populating and formatting the documents
Because of the lengthy process of FDA Compliance for MedTech and Medical Devices, the regulatory body has divided their approval process into the following 4 stages:
- Classify devices and understand regulations
- Select and prepare premarket submissions
- Send submissions to the FDA for review
- Comply with regulations post approval
To help medical device companies expedite this process and to ensure error-free submission with accelerated time-to-market, they can employ generative AI and RPA capabilities. Below are the ways how generative AI and RPA can revolutionize the FDA Approval process.
Use of Generative AI and RPA in all 4 stages of FDA compliance:
Stage 1: Classify devices and understand regulations:
There are 3 classes of wearable medical devices in the market:
- Class I devices are low-risk devices
- Class II devices are intermediate-risk devices
- Class III devices are high-risk devices that are very important to the health or sustaining life
The compliance and regulatory requirements for each class of device are different. Your regulatory team must identify which class your wearable medical device falls in and the safety and data regulations that are relevant to your device.
To accomplish this and to create a roadmap for generating and publishing these documents to FDA, you can employ your regulatory team with generative Copilot AIs to classify your product and to find the right information about safety and efficacy from large data sets.
Stage 2: Select and prepare premarket submissions:
Many wearable medical device companies that wish to sell in the US markets must submit a Premarket Application (PMA) to get FDA 510(k) cybersecurity approval premarket to ensure medical device cybersecurity readiness. Along with the application, they must provide the following documents:
- Threat modeling
- Device and software Cybersecurity risk assessment report
- Medical Device software security testing and assessment reports
- Complete vulnerability assessment for third-party software (if required)
- A detailed plan for continuing cybersecurity support
These documents are to be prepared for each market and to accelerate this process, regulatory teams can use RPA to reduce the task redundancy and use AI to auto-populate forms. This also removes the possibility of human errors from the process and allows your regulatory team to focus on integral documents.
Stage 3: Send submissions to the FDA for review:
Before sending the documents to the FDA, you can use AI models to scan all the submitted documents and their content to detect inaccuracies and wrong information. AI can flag these contents and help you save time and effort for resubmissions.
Sage 4: Comply with regulations:
Cybersecurity in medical devices is one of the biggest problems that they face even today. With the use of AI, companies can enable continuous monitoring of devices and identify potential cyber threats as well as data breaches.
Envision AI as a compliance enabler:
To put things in a nutshell, all we have to do is think of AI as an enabler and use its generative, predictive, or process automation capabilities to convert your challenge into an opportunity.