In December 2020, we posted about the MHRA’s draft guidance on randomised controlled trials generating real-world evidence (RWE) to support regulatory decisions.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Following a public consultation on the draft guidance, the MHRA issued its guidance at the end of last year in the form of two papers: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.

Introduction to RWD Guideline Series

The RWD introduction provides an overview to the MHRA’s RWD guideline series, including points to consider when evaluating whether a RWD source is of sufficient quality for the intended use.

When planning a study using RWD, it is important to demonstrate that the data source is of sufficient quality for the intended use, and that general principles relating to the strength of evidence produced by a study have been applied. As such, the principles used in traditional clinical trials (for instance, the importance of randomisation and blinding)  remain applicable for studies using RWD.

In particular, the introduction to the guideline series emphasises the importance of the quality of the source data, including its accuracy, validity, variability, reliability and provenance. For example, it states that data quality processes and checks must be detailed in the study protocol and appropriately validated. Published guidelines for good database selection from other fields, including pharmacoepidemiology, are also applicable and provide useful guidance for RWD collection. Sponsors should give due consideration to the source population prior to submitting the study protocol to ensure it is appropriate, along with any potential interoperability issues between healthcare systems in the devolved nations in the UK and internationally. All parties, including, where possible, those generating the source data, should understand their respective responsibilities with respect to the collection, maintenance and use of RWD.

One important point to note is that the MHRA Good Clinical Practice (GCP) may also apply. In particular, inspections are generally carried out under the risk-based compliance programme, and areas of particular interest for inspection of RWD suppliers and management of RWD data include: randomisation methods, data management, investigational medicinal product (IMP) management, safety reporting, sponsor oversight, the collection of study data from external providers when applicable, and the processes used to ensure the quality of the reported data.

RWD Guideline

The first guideline in the series relates to randomised controlled trials using RWD to support regulatory decisions. The MHRA notes that the guideline is applicable to trials in any area; however, the sections on trial approval are currently specific to medicines. This is due to ongoing revisions to the UK medical devices regulations (discussed in a previous post).

The guideline covers clinical trial authorisations (for trials run wholly or in part of the UK) and clinical trial design, including choice of endpoints and safety data requirements. The guideline does not cover other types of studies that could be run using RWD, such as observational studies or clinical trials using RWD as a control arm.

Trials that fall within the definition of a clinical trial in the Medicines for Human Use (Clinical Trials) Regulations 2004 will need to be authorised accordingly. The fact the trial is being conducted from a RWD source does not change this. However, where the potential risk associated with the IMP is considered no higher than that of standard medical care, known as a “Type A” trial, this may benefit from some flexibility, such as around the requirements for safety reporting.

Provided the data quality is robust and the trial is well-designed, the evidence generated from randomised controlled trials using a RWD source is not generally considered less valuable for regulatory decision-making compared to evidence from traditional clinical trials. However, it remains the case that data from randomised trials using a RWD source are most commonly used for label changes for licensed products, including for drug repurposing. The MHRA hopes that the use of RWD in support of a wider range of trial objectives, including the investigation of new products, may be possible with appropriate safeguards.

Next steps

Sponsors interested in the use of RWD in their development programmes are encouraged to engage with the MHRA for further advice on specific proposals. Sponsors may also seek advice by requesting a scientific advice meeting.

At present, it is unclear when the MHRA will publish further guidelines in the series, or on what topics.

Update from the EU

There is a growing level of activity and planning around the use of RWD in this arena globally. In particular, in the EU, a Joint Big Data Task Force by the European Medicines Agency (EMA) and the Heads of Medicines Agencies (HMA) was set up in March 2017. In January 2020, it published a report with ten priority recommendations, which aimed to introduce to the EU regulatory framework the tools and methods to establish the progressive use of RWD in decision-making. In 2020, the Joint Big Data Steering Group replaced the Joint Big Data Task Force and took over the task of implementing the ten priority recommendations.

One of the most important recommendations is the creation of the DARWIN EU network, a platform which will allow access and analysis of healthcare data from across the EU. The DARWIN EU network is a challenging project from an operational, technical and methodological perspective. It  aims to serve as a platform that provides access to databases of known quality and content such as electronic health records, registries, claims databases, hospital data etc. The number of databases accessible through the DARWIN EU network is expected to evolve and expand over time.

On 9 February 2022, the EMA initiated the establishment of the DARWIN Coordination Centre. The role of the Coordination Centre will be to develop and manage a network of RWD sources across the EU and to conduct scientific studies requested by medicines regulators and, at a later stage, requested by other stakeholders. All studies will be published in the EU catalogue of observational studies. According to the EMA, the first DARWIN pilot studies will be delivered in 2022. The DARWIN EU network is also expected to contribute to the development of the European Health Data Space (see our previous blog post on the proposal for a Regulation by the European Commission).