There is currently no specific legislation in the UK that governs AI, or its use in healthcare. Instead, a number of general-purpose laws apply. These laws, such as the rules on data protection and medical devices, have to be adapted to specific AI technologies and uses. They sometimes overlap, which can cause confusion for businesses trying to identify the relevant requirements that have to be met, or to reconcile potentially conflicting provisions.

As a step towards a clearer, more coherent approach, on 18 July, the UK government published a policy paper on regulating AI in the UK. The government proposes to establish a pro-innovation framework of principles for regulating AI, while leaving regulatory authorities discretion over how the principles apply in their respective sectors. The government intends the framework to be “proportionate, light-touch and forward-looking” to ensure that it can keep pace with developments in these technologies, and so that it can “support responsible innovation in AI – unleashing the full potential of new technologies, while keeping people safe and secure”. This balance is aimed at ensuring that the UK is at the forefront of such developments.

The government’s proposal is broadly in line with the MHRA’s current approach to the regulation of AI. In the MHRA’s response to the consultation on the medical devices regime in the UK post-Brexit, it announced similarly broad-brush plans for regulating AI-enabled medical devices. In particular, no definition of AI as a medical device (AIaMD) will be included in the new UK legislation, and the regime is unlikely to set out specific legal requirements beyond those being considered for software as a medical device. Instead, the MHRA intends to publish guidance that clinical performance evaluation methods should be used for assessing safety and meeting essential requirements of AIaMD, and has also published the Software and AI as a medical device change programme to provide a regulatory framework with s a high degree of protection for patients and public.

Continue Reading UK Policy Paper on regulation of AI

In December 2020, we posted about the MHRA’s draft guidance on randomised controlled trials generating real-world evidence (RWE) to support regulatory decisions. As we noted in our previous blog, although real-world data (RWD) are widely used to monitor the performance of medicines and devices in patients after regulatory approval, RWD have been utilised much less frequently to demonstrate the safety and efficacy of a product at the stage of initial authorisation. The MHRA aims to provide sponsors with points to consider when planning to conduct clinical trials using RWD sources, and to provide information on the design of studies seeking to generate evidence suitable for supporting regulatory decisions. It is hoped that a greater use of RWD, and more uniform collection and use, will accelerate the availability of cost-effective treatments and reduce the time and cost currently required to generate relevant data.

Following a public consultation on the draft guidance, the MHRA issued its guidance at the end of last year in the form of two papers:

  1. An introduction to the RWD guideline series; and
  2. The first guideline in the series, on planning a prospective randomised controlled trial using RWD sources with the intention of using the trial data to support regulatory decisions.

The intention is for the MHRA to publish further guidelines in the series in due course.

Continue Reading Use of Real-World Evidence in the UK

The UK’s Medicines and Healthcare products Regulatory Authority (MHRA), the US Food and Drug Administration (FDA) and Health Canada have recently published a joint statement identifying ten guiding principles to help inform the development of Good Machine Learning Practice (GMLP).  The purpose of these principles is to “help promote safe, effective, and high quality medical devices that use artificial intelligence and machine learning (AI/ML)”.

The development and use of medical devices that use AI and ML has grown considerably over the last few years and will continue to do so. It has been recognised that such technologies have the potential to transform the way in which healthcare is deployed globally, through the analyse of vast amounts of real-world data from which software algorithms can learn and improve. However, as these technologies become more complex and nuanced in their application, this brings into question how they should be overseen and regulated. Crucially, it must be ensured that such devices are safe and beneficial to those who use them, whilst recognising associated risks and limitations.

Continue Reading Ten International Guiding Principles on Good Machine Learning in Medical Devices

The UK MHRA has issued draft guidance on randomised controlled trials generating real-world evidence (RWE) that is used to support regulatory decisions. It is intended to be the first in a series of guidance documents addressing RWE. The guidance is part of the MHRA’s push to reinforce the view of the MHRA as a pro-innovative regulatory authority, and that the UK is a leading country in which to conduct clinical research, post-Brexit.

Continue Reading UK MHRA consultation on real-world evidence

On 12 October 2018, the MHRA issued Guidance for products without an intended medical purpose (Annex XVI) under the new Medical Device Regulation (EU 2017/745) providing guidance on the expansion of scope of the medical devices regime to include certain products which had been previously unregulated at EU level.

Article 1(2) of the Medical Devices Regulation (MDR), in force from 25 May 2017, explains that the MDR will regulate “certain groups of products without an intended medical purpose” as though they were medical devices.

There are currently six types of products in this category which are listed at Annex XVI of the MDR.

Continue Reading New MHRA guidance on non-medical devices