Made possible by the mobile health revolution and Internet of Things (IoT), the use of Real World Evidence (RWE) is emerging as the new frontier of medical research and innovation.
“After the lord mayor’s show comes the dust cart,” the saying goes. In other words, substance always outweighs show. That is certainly true in medicine where the use of empirical data is not new. Since the 1970s and the implementation of pharmacovigilance systems, feedback from the “field” has been one of the means used to improve pharmaceutical research and health decisions. This is nothing compared to the coming revolution.
In 2020, we will produce nearly 1.7 megabytes data per person per second, a good part through the connected medical and consumer devices! In this Himalaya of data, whole swathes of medical information will be established and are already established: parameters stemming from activity sensors, connected blood pressure monitors and other glucometers, data from mobile health applications, telemedicine software, and social networks. Still largely unexploited, this mass of data from life outside the clinical setting is known as Real World Data forming Real World Evidence.
The right treatment, for the right patient, at the right time! What does this change?
What does this change? Everything! However rigorous they may be, standardized clinical trials concern only a tiny fraction of patients. For its part, Real World Evidence comes from a far larger and far more heterogeneous population in terms of age, sex, comorbidity, physical condition, treatments undertaken over many years at times, genetic profile, and diet.
As has just been shown, the growing use of digital tools enables us to gather and make accessible an unprecedented volume of data on health. Moreover, the emergence of artificial intelligence and algorithms enables us to analyze this mass of data to harness medical advancements unimaginable just ten years ago! The potential benefits are many: development and approval of new medicinal products and treatments, new indications for existing treatments, customization of health care, cost-benefits analysis of an innovative treatment for the long term, identification of unmet needs, better monitoring of side effects, measurement of the clinical and economic impact of interventions in the health system whilst achieving savings, development of new guidelines and decision-making tools for clinical practice, etc.
In the long run, properly used, Real World Data could enable us to reach one of the holy grails of medicine: the right treatment, for the right patient, at the right time!