We are living in the age of big data. Drug development companies are swimming in information that can inform their processes and assist them in bringing a treatment to market; but this information is no longer solely generated through clinical trials.
As the cost of healthcare continues to rise and companies face pricing pressures, there comes a growing need to demonstrate the benefits of a treatment outside the regulated environment of a clinical trial. So, companies are turning to real-world data (RWD) to demonstrate the value of their product on a real-world population.
What is real-world data?
Any insights into a treatment gathered outside of a clinical trial setting could be a source of RWD. Health records, wearable devices, healthcare apps, patient-recorded outcomes, even insurance claims all can provide evidence to support the effectiveness of a product. As it’s captured within the healthcare system itself, against real patients rather than trial subjects, it can provide an additional dimension to observations gathered during clinical trials.
Why is real-world data so important?
With a deeper insight into how treatments are being used and the effects of a drug, RWD can provide regulators the information they need to assess post-market safety and produce risk/benefit analysis; key enablers for regulatory decisions and market approvals. The data can not only inform decisions made regarding commercialisation, but can help inform those involved in research and development as to the needs and requirements of a patient population.
But the scale of data available does far more than help companies bring their treatments to market quicker. Importantly, it enables us to further understand the patient journey, and provides a huge opportunity for companies to improve patient outcomes. By producing RWD, patients act as integral participants in the future of their own healthcare.
What does the future of real-world data look like?
The sheer amount of data currently available is overwhelming; for one treatment there could be hundreds of thousands of seemingly relevant pieces of RWD, and most organisations lack the resources to effectively collect and analyse it, which is why we’re seeing larger firms invest in machine learning technology or partner with start-ups specialised in AI. We’re also seeing a rise in demand for professionals with RWD/RWE experience.
Some of the larger industry players will follow in the footsteps of companies like IQVIA, in establishing and developing their own RWD capabilities and offering. We’ll see more cross-departmental collaboration, among physicians, pharmacists, statisticians and pharmacologists, as we work to discover new ways of collecting and analysing RWD.
Advances in cloud-based technology, artificial intelligence, and automation could help smaller firms discover the benefits of using RWD. Providing them with more access to information about who their treatments effect, in what context, and at what price, will shorten their product pipeline and enable faster patient access.
Ultimately, continued data openness will enable companies to develop forward-thinking healthcare strategies, such as personalised medicine, which can address previously unseen problems and put the patient population at the heart of treatment production. As machine learning technology also advances, we’ll see healthcare professionals be able to make faster, more accurate diagnoses through access to this real-world data, and variables that might’ve been previously overlooked will be used to inform a deeper understanding of patients’ conditions.