Robotics: Regulatory Trends

GlobalData Thematic Research 28 July 2020 (Last Updated July 28th, 2020 10:13)

Robotics: Regulatory Trends

Robotics within healthcare is entering the space by passing through current regulatory frameworks that were put into place for medical devices. However, as these robots become prominent, specific regulatory frameworks will need to be developed in order to ensure efficacy and patient safety. The most tangible forms of regulation will come from regulatory bodies that are already in place, such as the FDA and the European Medical Devices Directive.

Listed below are the key regulatory trends impacting the robotics industry, as identified by GlobalData.

FDA

The FDA categorises medical devices on a class system based on the invasiveness to patients. The more risk there is to a patient, the more regulation required for those devices. Robots will most likely follow the established premarket and class system frameworks set forth by the FDA. As the products proliferate, varying from care robots to rehabilitation robots, the regulatory process will remain stringent in terms of getting these products on the market.

The da Vinci system received 510(k) clearance in 2000; thus most of the robotic surgical systems are under that regulatory certification process. The Senhance System received its 510(k) approval in 2019 and can be marketed and sold within the US. It took the FDA four months, one week, and two days for Senhance to get 510(k) approval.

FDA – the Digital Health Innovation Plan

The FDA has taken initiative to categorise and classify digital health products in order to better regulate and manage software healthcare solutions. The Digital Health Innovation Plan (DHIP) outlines guidance for hospital institutions under the recommendations of the Center for Devices and Radiological Health (CDRH). The DHIP has three clear directives: building expertise through the CDRH’s digital health unit, providing clarity by issuing guidance on medical software provisions, and launching a precertification program in order to create a framework for digital health technology oversight.

The DHIP caters to healthcare software from diverse categories such as cybersecurity and AI. The DHIP also takes into account issues that can arise with security with healthcare data and interoperability of software. The initiative takes efficacy into account and the framework would take a risk-based approach when categorizing healthcare AI products.

The DHIP also includes the Digital Health Software Precertification Program. The precertification program is an ongoing pilot study that began in 2017 and includes a diverse set of manufacturers from the tech and conventional healthcare industries. The FDA rolled out its Digital Health Innovation Action Plan (DHAIP), which focuses on the quality, safety, and efficacy of digital health products. Within the DHIAP, the FDA initiated a volunteer pilot program to regulate the digital health software industry. The FDA would also like companies to demonstrate their Culture of Quality and Organization Excellence (CQOE), which basically means engaging in ongoing efforts to establish internal frameworks and processes pertaining to digital software.

The initiative from the FDA is a move in the right direction, as the Precertification Pilot Program creates an initial framework that will enable some sort of regulation framework for AI.

FDA – Software as a Medical Device

The FDA also has another way to categorise software being used in medical devices. This risk-based categorisation resembles the conventional class system the FDA uses. Software as a Medical Device (SaMD) covers software within a healthcare context in its entirety, meaning simple software used in magnetic resonance imaging (MRI) machines and complex AI systems used in healthcare are managed by this class system.

If the software is an integral part of the device such that it is not separable, then it would be cleared/approved with the parent device and have the same classification. If the software functions more as an accessory to the parent device, it could be cleared/approved separately and have its own classification.

Canadian regulations

The Canadian government is aware of the role that technology, specifically automation and AI, will play within their burdened healthcare system. The Canadian federal government already utilises a risk-based framework to regulate medical devices. The Medical Device Regulations under Health Canada have approved and issued attainable licenses for AI innovations within the country. There are 14 recommendations that have been made to incorporate AI into the Canadian healthcare system.

Equivalent to HIPPA within the US, the Canadian Personal Information Protection and Electronic Documents Act (PIPEDA) encompasses patient privacy. PIPEDA will need to be implemented in some form, as AI deals with sensitive health data.

European regulations

All healthcare robots will go through Conformité Européene (CE) Mark certification under the European Medical Devices Directive (92/42/EEC). The class each robot is categorised under depends on its invasiveness in regard to its role within a healthcare environment. For example, the newest da Vinci X system from Intuitive Surgical recently acquired the CE Mark approval as a class 2b CE 0543 device.

The EU does not have similar AI technology adoption rates to those seen in the US. However, there has been an influx of interest in AI use within a healthcare setting in the EU. Healthcare systems within the EU would like to implement AI to aid in workflow assistance, oncology, and radiology.

APAC regulations

The established frameworks within specific Asia-Pacific (APAC) countries will be the mainstays in the oversight of robotics. For example, the Japanese Ministry of Health, Labour and Welfare (MHLW) controls device regulation with a framework that is similar to the class system used in the FDA, EU, and Canadian frameworks. Last year, the da Vinci system received approvals for colorectal, gynecological, and thoracic surgeries, plus gastrectomies, bladder cystectomies, esophagectomies, and mitral valvuloplasty.

This is an edited extract from the Robotics in Medical Devices – Thematic Research report produced by GlobalData Thematic Research.