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Seizing opportunities in the next steps for real world evidence

Published on 15/01/18 at 11:12am

Real world evidence is high on the agenda at many conferences, as people mull over the possibilities that it may hold for changing the way we track a particular medicine's efficacy. Matt Fellows has compiled some of the latest thought leadership on the challenges that lie ahead for wider adoption of the technology.

Efficacy data is what drives the pharmaceutical, medical and healthcare industries and beyond. Alongside safety data, it is the key arbiter of a medicine’s effectiveness in its primary purpose in the world, and is the essential commodity that clinicians and other professionals trade in. And the vehicle that delivers this commodity is, of course, the clinical trial, which has reliably generated such data through, in the best circumstances, carefully constructed studies based on sound science with a wide and representative participant population. 

But, in today’s climate where efficacy and safety of healthcare treatments are increasingly scrutinised, and rightfully so, is this traditional process and dataset enough to achieve the highest standards that we expect? There is a consensus in the industry that the answer to many of the problems that arise from this methodology can be found in real-world data (RWD), and the real-world evidence (RWE) which can be drawn from them.

This was one of the centre points of the seminar ‘Realising the potential of real-world evidence’ at the recent Global Pharmaceutical and Biotechnology Conference held by the Financial Times in London, where key figures from the field came together to discuss their experience of RWD and RWE and how they felt stakeholders could capitalise on their benefits moving forward. In attendance on the panel were Pfizer’s Andy Schmeltz, Senior Vice President, Patient & Health Impact Group; GlaxoSmithKline’s David Leather, Medical Vice President for Respiratory Franchise; and Matt Cooper, Business Development and Marketing Director, Clinical Research Network at the National Institute for Health Research, chaired by Deloitte’s Global Life Sciences & Health Care Industry Leader, Greg Reh.

Promising potential

In many ways, particularly in terms of adoption, RWD and RWE can be considered to be in their embryonic stages, despite their presence throughout the past decades. However, as the panel attested, now is the time when these tools are truly presenting essential and untapped opportunities for stakeholders. As Schultz noted: “RWE is not a new concept, but this is an exciting moment in time. With exponential advances in technology, data capture, data access, data storage, and approaches, leveraging artificial intelligence and machine-based learning, the potential for RWE is tremendous.

“There’s end-to-end opportunities across the drug development and distribution continuum. From basic research identifying populations within a disease who can benefit most, to our clinical trials paradigm where we can simulate, using RWD, inclusion/exclusion for trials, as well as identifying the position to recruit trials, this can really speed clinical development timelines and keep costs down.

“Once a medicine is approved by regulatory authorities, RWE can be used by healthcare professionals to identify the utility of medicines in sub-populations not studied in clinical trials, and enable publications to better inform the healthcare community at a pace that just wouldn’t be possible using traditional trials.”

It is clear that industry players stand at a unique point in the life of RWE as it just begins to show its true potential, but this in itself presents entirely new challenges. David Leather believes this will be a period of rapid change, and industry players will be tested to keep up pace with innovative solutions.

“The way I see it at the moment is that we’re in a dilemma in a way,” he explains. “For years people have been asking for help in taking efficacy studies and translating them into what value that will bring in the real world. That could be clinicians, guideline writers, payers, HTA groups, and the industry itself.

“The real-world space now is moving very fast, and that is largely driven by the digital growth, electronic health records, RWD and partnerships that have emerged very strongly recently. The dilemma is that the very people who asked for it are not keeping pace with the speed. The paradox is how fast the space is moving, and how do we move to keep up with it?”

Leather also touched on how effective use of RWE can mitigate the shortcomings of the traditional clinical trial model: “The world is locked into scientific robustness of efficacy trials. Our guidelines are based fundamentally on double-blind randomised control trials that are highly selective – probably less than 5% of the general population make it into them. So our guidelines are based on evidence that only relates to 5% of the patients who will get the medicines.”

Leather highlights a key problem that has been struggled against for a long time: traditional clinical trials are not adequately representative. For instance, as recent as November this year, the Journal of Women’s Health found that white individuals made up 77.2% of the total participants in US trials, with ethnic minorities making up the remaining 20.3% - a significant problem when racial or ethnic minorities actually make up close to 40% of the US population. Deriving data from the wider world outside clinical trials from sources such as electronic health records, RWE is able to paint a much more complete picture of how a particular medicine may affect a particular patient group.

Hurdles to overcome

The industry is under no illusions when it comes to the benefits of RWE, but many obstacles to wider adoption still remain. An audience survey at the event revealed a general consensus among those present that access to external data was the foremost hurdle in widespread RWE adoption. However, on personal experience, the panel did not agree. “My experience is that you can access datasets under the appropriate guidance and the right partnerships and patients will consent,” Leather mused, while Schultz added: “I think the issue is more detailed than ‘access to external data’. It’s the interoperability of data sources. Simple things like some data sources saying man/woman and other sources saying male/female, and getting those to talk to each other […] For instance, the connecting electronic health records with fulfilment of prescription data. All the data is out there, it just doesn’t talk to each other.”

Matt Cooper agreed, remarking: “There is a growing desire for greater use of RWE, and there must be greater research that gets put behind enhancing those capabilities, whether it’s on a national or global level […] to allow those different datasets to be aggregated, to talk to each other and be searched together on similar terms – that would be hugely powerful.

“There is a huge amount of rich data out there, but they are at the moment in different collections – we need that ability to pull them together, for the regulators to then be satisfied by how the sets have been built and the robustness of the data.”

The notion that regulators must be on board with this direction was key to the discussion, and this raises the question of standardisation. Currently, there is a lack of clarity from regulatory bodies on how they will accept and incorporate RWE in a marketing authorisation, and as a result this leads to RWE being undervalued in the approval process, as well as making it difficult for sponsors to include it as part of their submissions. This is a clear area for improvement moving forward, as Schultz commented:

“There’s an opportunity certainly for consortia to share learnings to set the right standards, because it’s just inefficient for companies with the best of intent and different partnerships to go down a path when there’s not validation of the common standards. I think that’s the biggest opportunity, certainly from a regulatory stand point.”

On this particular segment of the argument, Pharmafocus spoke to Nick Ibrahim, Marketing Director for Vifor Pharma UK, who gave his thoughts on the subject:

“I don’t know if common standards need to be put in place, but I think collecting data on a regular basis, and looking at it to see what it’s telling you, should be fed into the regulatory system to make sure updates are achieved. This is currently a slow process. The credence on Real World Data is not given as it should be. There should be a regular review process, mining Real World Data from all sources to see what can be learned and how it can be expedited by the regulatory system. This would allow us to act on learnings and ensure patients get the best use of treatments.”

While this clarification on the part of the regulators could prove to be greatly beneficial, Schultz was keen to point out that despite the benefits they can bring, RWD would still remain the gold standard at the heart of the regulatory process, particularly until this clarification has been standardised.

“Clarity from regulators would certainly be helpful, but I want to be clear, although we’re very excited about the promise of RWD, randomised controlled trails are going to continue to have an important role,” he said. “Until there’s more clarity, the investments in RWE are layered on top of the core investments in the way we do drug development. Perhaps there is a future where we can moderate that level of investment so that it is shared, but certainly I think we benefit from time, speed and cost.”

Securing the right talent

Another key area which arose in discussions was the issue of recruitment and its relationship to greater adoption and significance of RWD and RWE. Pushing for greater adoption is not as simple a task as it may seem, particularly as experts adept at interpreting RWD are not necessarily commonplace; attracting talent that has the right skillsets can prove problematic.

“The reality is that we don’t have the right technical expertise inherent, historically, in the life sciences companies to tap into,” Schultz explained. “So we have to source talent – data analysts, data scientists – from other places. What are the companies that have already capitalised on analogous data? Financial services and e-commerce companies talk about other companies where their business model is anchored in Google and Amazon, but we have to make the case for why a career in life sciences, in biopharmaceuticals, is the right destination, rather than any of these other similarly sexy industries. I think there’s an opportunity to recruit and the calling of working on solving and advancing the healthcare paradigm – helping patients, helping healthcare systems which are in the news every day – has to be the mechanism to do that.”

Leather agreed, suggesting that greater adoption in itself would help to tackle the problem by giving more prominence to RWD: “Understandably, statisticians, whether they work in industry or in a regulatory group or payer group, are not used to this type of dataset, and there assumptions made about it: ‘it’s all noise’, ‘it’s all social work, it’s not science’. That’s definitely an issue and people are moving forwards with that. The more we produce this data, the more it gets published and shared and the more chance people have to see it and make sense of it alongside efficacy data.”

Opportunities ahead

The panel’s expertise and experience in the field proved to greatly illuminate the problems and challenges that lay ahead to adequately brandish RWD and RWE as core tools in the arsenal of stakeholders in order to truly realise their potential. And of course, the benefits are clear and stretch well beyond what may appear at first glance.

Schultz in particular was energised by the sheer breadth of prospects they present, and detailed in short how their adept use could prove to be transformative beyond the avenues already touched upon.

“What I’m most excited about the prospect is shifting from this volume-based healthcare paradigm to a value or impact-based paradigm,” he remarked. “The currency, historically, has been volume or quantity of healthcare delivered, and hopefully in this new paradigm, it will be the quality or the outcomes of healthcare that’s measured and delivered, and certainly, RWE is going to have a key role to play in that.

“We are moving from reactive uses of our data to more proactive, and with machine-based learning and cognitive computing, there can insights generated where we didn’t even contemplate asking those questions. I think when we get there, that’s really where the utility of RWE is going to take off.”

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