The real-world data conundrum

No matter how we look at it, our approaches towards medicine are changing. This change is affecting all stakeholders. From a drug development perspective, a new data science is driving a paradigm shift in the product life cycle. We can see how manufacturers and healthcare systems are looking at the quality and relevance of their data and how they combine these with behavioural and social data. We are entering the new phase of data-driven health provision. It is a brave, new (real-) world.

As with every substantial shift and phase in the history of medicine, it takes a structured and collaborative multidisciplinary approach to look to the future and capitalise on the opportunities brought by data. ‘Real-world data’ is a collective term that includes a variety of sources ranging from electronic health records and health surveys to registries and administrative data. The term has expanded to include a variety of routinely available social, economic and other systems data, as well as data from apps and digital products. While the variability in quality and availability is enormous, big data always comes with great expectations.

The stakeholders

At the forefront of innovation around real-world data is the industry. And its stake, finance-

and opportunity-wise, is huge. There is some ambiguity as to what the actual cost of developing a new drug and bringing it to the market is. Our best guess comes from the studies undertaken by the Tufts Center for the Study of Drug Development, which in its latest calculations estimates this figure at $2.558bn. While there are debates as to whether this figure is accurate and transparent, other calculations have had limitations as well, most notably due to not including the cost of capital estimates. But where the financial challenges start for several pharmaceutical companies is the cost of failure, and there still seems to be a 90% failure rate in the clinic. Regardless of what the actual total costs are, though, it is certain that, with very few exceptions, the era of blockbuster drugs is over and the demand for stratified medicines, affordable treatment options, access for populations in developing countries and an up-to-date evidence-base is ever increasing.

At the core of this spectrum are patients. As the understanding of stratified, personalised medicine has grown over the last decade, a promise has emerged that there will be a time when healthcare professionals will be able to provide the right treatment, for the right person, at the right dose, at the right time. Is this realistic? Or rather, is this within our grasp? The high levels of innovation understood in the pharmaceutical industry, and some recent progress in life expectancy, have also created a promise around treating rare diseases. However, there is still high unmet need: fewer than one in ten patients with a rare condition receive disease-specific treatment and approved medicines are available for only 5% of rare diseases. At a more fundamental level, though, availability in the public sector of essential medicines (ie those that satisfy the priority healthcare needs of the population) in 27 developing countries with available data is only 34.9%. Thus, there are ongoing issues with and conversations about - not limited to developing countries - pricing and affordability of drugs.

For payers, the goalpost in product development has moved from approval to reimbursement and it seems critically important that pharmaceutical companies generate data to achieve optimal reimbursement as opposed to just focusing on product approval. The value of real-world data to payers is that it increases the certainty about the effectiveness of the product that they’re buying. Similarly, regulators are now increasingly growing to appreciate that real-world data, typically collected for non-regulatory purposes in electronic medical records, registries and administrative and claims databases, may provide new insights into the performance, clinical outcomes and safety associated with medicines use. Indicatively, in the US, the FDA has recently published recommendations on the use of real-world data for regulatory decisions, whereas in the UK, the MHRA has been hosting the Clinical Practice Research Datalink (CPRD) for almost 20 years.

Bridging the gaps

With the pressure on the industry to provide economic value and also to better understand how patients will respond to therapies from the outset, all sides have to think more carefully about how they approach real-world outcomes. The opportunities are clear. Pharmaceutical companies can reduce the cost of running randomised controlled trials and benefit from analysing routinely collected data. Payers are starting to understand that real-world data gives them more certainty around the product that they are buying, in regards to its effectiveness and safety. The data generated from the participating patients in a phase III clinical trial is very different from the outcomes in real-world patients, therefore the value of the related product is going to be different. It’s the same for regulators, especially around long-term safety, monitoring adverse effects and establishing effectiveness. All of this can be particularly complicated when it comes to real-world patients, with the challenges of an ageing population and rates of multi-morbidity.

Studies (including a review from my team in 2016 published in BMC Health Services Research) now show that evidence from real-world data is increasingly used to inform published guidelines and guidances. The increased uptake in recent years, as well as an increase in the conduct of pragmatic trials, shows that this area of healthcare is changing and we are experiencing a phase in this transition. To address expectations and capitalise on the value of real-world data, pharmaceutical researchers need to ensure they undertake research of translational value to the healthcare community, which will give a more realistic view of how a drug works in actual healthcare settings.

The window of opportunity is open. Public trust is considered by many to be the biggest challenge for the commercial sector. However, a comprehensive study (by Ipsos Mori and the Wellcome Trust in 2016) has shown that most of the general public tend to accept commercial sharing of health data and acknowledge that a regulated pharma sector helps public healthcare and needs data to do its job.

With patients and governments, payers and regulators, all having a vested interest in the success and efficiency of the pharma life cycle, pharmaceutical companies are under pressure to justify many aspects of their products to these diverse stakeholders. Encouragingly, we are noticing them increasing their relevant capacity and expertise. All parts of the healthcare system now need a way to efficiently receive, integrate, understand, compute and use digital health data from health and social encounter locations. This will require the merging of what is often disparate data from multiple sources. We are definitely moving in this direction. The question is how fast we can get there and how quickly this can become cost-effective for all involved.

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