At the height of the COVID-19 pandemic, these capabilities were put to the test, being used to compare hospital caseloads to research activity in real-time and enabling COVID-19 clinical trials to rapidly recruit participants across the UK.
Having demonstrated the possibilities when multiple agencies work together towards the same single goal – solving a pandemic – one disease/virus, researchers have an understanding of how this model could work. However, expanding that model to cover all data in all disease areas is a monumental and highly ambitious task.
In the UK, research organisations and pharma companies are working to find ways to reach this goal, using data to inform commercial clinical research now, and how this foundation can be built upon in the future. This was the focus of a recent pharmaphorum webinar, held in association with the National Institute of Health and Care Research (NIHR) where experts from the NIHR and Roche discussed the potential of healthcare data in commercial clinical research.
While data is an asset across the research landscape, speakers spotlighted site selection as an area where data can be particularly valuable.
“This is about doing research in the right place at the right time,” explained Professor Caroline Wroe “We know that there is an inverse care law, the people that need our help the most are the least likely to access it.”
“It would be fantastic if we could shift that paradigm when we are talking about research. If we can put that resource where it is most beneficial then that is a really good starting point.”
Why is data important?
In the early stages of planning a clinical trial, one of the most important considerations is site selection. Identifying the best location for a particular trial can have a direct impact on the development of a study as it progresses, but there are a number of variables that have to be assessed to ensure that the right study is placed at the right site, at the right time.
“Data is becoming an essential element in early decision making around clinical trials both in terms of the countries that are selected to take part but also sites that take part,” explained Roche’s therapy relationship manager, oncology, Ed Merivale. “It provides great insight into where our trials may be most successful, which patient groups have the most clinical need and the best ways for us to design and deliver those studies.”
Historically, site selection was often influenced by experience and relationships between pharma companies and researchers. According to the head of business intelligence for the NIHR’s Clinical Research Network, Stephen Lock, this is an understandable approach, as prior knowledge of a sites working patterns and experience can be an asset, allowing companies to focus on meeting specific trial goals and timelines. However, as noted, this may have also biased companies against exploring more suitable partnerships:
“With all those pressures we can become a little bit blind to some of the other choices that are available to us, and that’s where data can really help.”
Using site selection data, researchers are empowered to plan clinical research in locations that offer the best resources, access to patient groups, and expertise for that particular study.
Lock highlighted the NIHR’s work with data in diabetes as a notable example of how data can be used to inform site selection. “We have worked a lot with data that comes from public health England, which could show the prevalence of diabetes across the country. What we can do is take that data and we can contrast that with patterns of recruitment into diabetes studies.”
Moreover, the panel noted that pharma companies can use data to identify sites that are not already taking part in studies. By utilising these sites, researchers open up trial access to a wider pool of participants, who may have been unable to take part in previous studies due to personal, distance or time restraints. As these areas are unlikely to be saturated, their inclusion offers enhanced recruitment potential.
“We have worked a lot with data that comes from public health England, which could show the prevalence of diabetes across the country. What we can do is take that data and we can contrast that with patterns of recruitment into diabetes studies.”
The current data landscape in commercial clinical research
Although data is one of multiple considerations that companies assess when planning commercial clinical research, as the data matures and becomes more accessible, companies have a wealth of valuable information to draw from. Within the UK, sources can provide detailed information about factors, such as disease epidemiology and population level data that can impact how and where clinical research takes place.
“There is a huge amount of publicly available data, but it needs reformatting, presenting, and interpreting to highlight where in the UK we should focus our recruitment efforts,” explained Merivale. “It’s not just about placing the site in the right places, sometimes we can’t do that, but also how we tailor the recruitment efforts in and around the sites that we do have. All with the ambition to ensure that we are enabling representative enrolment.”
Building upon this, Merivale noted that using data to model historical recruitment by ethnicity vs catchment area could potentially produce a profile model, which companies could use to predict the diversity profile of new studies.
In the UK, the NIHR has also witnessed the growing importance of data in the research space. As Lock highlighted, while the NIHR’s Clinical Research Network is predominantly responsible for the delivery of research, there has been an increasing interest in using the network’s knowledge and data to help advise upstream.
“We have a lot of data on what has and hasn’t worked historically, and there is a lot that we can infer from that data,” explains Lock. “With that we can really help the company to understand that they may want to consider somewhere like Blackpool in addition to Oxford or Cambridge.”
To illustrate how the Clinical Research Network can support a study, Wroe spotlighted the recent RELIEVE IBS-D trial. In this example, data played a significant role in identifying where irritable bowel syndrome with diarrhoea patients were located and how to access potential participants.
“We worked with the chief investigator to facilitate data searches in primary care so that we get really good feasibility and that means that you can pick sites where you have high numbers of patients and will likely have a high success rate in terms of recruitment.”
Additionally, Wroe explained that this information about the patient population offered insights into potential barriers and facilitators – both of which could be planned for in advance.
What’s next for healthcare data in commercial clinical research?
Although COVID-19 disrupted the status-quo of commercial research in the UK, panel members agreed that the pandemic demonstrated the potential of data and digital in clinical studies. The situation was certainly a unique one, with the majority of research efforts directed at one specific disease, however there are a number of lessons learned over the past two years about how companies identify and support site selection and trial recruitment that can be applied to smaller studies across multiple areas.
For Wroe, the NIHR-funded Platform Adaptive trial of NOvel antiviRals for eArly treatMent of COVID-19 In the Community (PANORAMIC) study is a notable example of how digitally enabled feasibility and recruitment can be effectively used to drive clinical research. With nearly 17,000 participants recruited over a three-month period, in early 2022 the study became the UK’s fastest ever recruiting interventional clinical trial to be delivered through primary care.
Digital literacy was also highlighted as an important element as pharma companies look ahead to future commercial clinical research. As Wroe noted during the webinar, “There is something that is so important about digital literacy, that we learn how to use this data comfortably and understand how we interact with our commercial partners to make best use of data.”
Another area where data has gained significant recognition is in precision targeting of rare disease patients. According to Merivale, there are many opportunities for development in this space, particularly in terms of connectivity at the point of identification and trial matching. Building on the progress of genomic lab hubs and with the right resources in place, he explained that researchers may reach a point in the future where data flow highlights mutations in real time.
Creating a foundation for future developments
While there are many areas where data can be used to improve the success of research, both the connectivity and application needs to be further developed to ensure that data can be readily translated into insights to improve commercial research delivery.
Optimising the data available for commercial clinical research is not something that will happen overnight. This is particularly evident in the UK, where the ‘richness’ and value of NHS data is often highlighted as a beneficial feature. Here, panellists emphasised the need to extract and share insights to realise the UK’s potential as a world-leading location for delivering research.
Lessons learned throughout the COVID-19 pandemic can provide a solid foundation to enhance and improve the use of NHS data. As Lock highlighted in the webinar, NIHR’s network model served as an important asset as the industry adapted to changes in research.
“The power of a network is way more than the sum of its parts,” he explained. “We’ve seen huge changes in the way that research is conducted in a way that would be impossible if you direct-funded into organisations.”
As we move beyond the pandemic, attention is beginning to turn to how this data-driven and collaborative research approach can be applied to other areas of healthcare.
As Wroe explains, “If we can take the learnings from COVID research about how we identify participants and support recruitment this will be an asset across other disease areas and geographies.”
