In recent years, we have seen an explosion of wearable health devices, health monitoring apps, and other automated health-tracking tools. The availability and popularity of various biosensors have generated vast amounts of data, and the pharmaceutical and healthcare industries are finding new ways to leverage this data to learn more about health, disease, and long-term outcomes of various interventions. Here are the ways that real-world data is innovating health. 

What is Real World Data (RWD)? 

Complete and accurate information is critical to advance scientific research and to inform healthcare decisions. Historically, data about the health and well-being of a patient is collected by asking questions or conducting tests, and documenting the results. This can be an excellent way to gather and track precise data (like blood pressure), but it is time-consuming and may be prone to error if the wrong questions are asked or inaccurate information is provided. 

Today, we are surrounded by an array of devices, tools, and systems that automatically gather and track various types of data about our bodies and activities. Every day, vast amounts of health data is generated, through means like: 

  • Patient care records
  • Insurance claims data
  • Mobile health apps
  • Wearable devices and sensors
  • Product registrations
  • Social media content
  • IoT-enabled devices

In the healthcare industry, this information is known as Real World Data (RWD), and is contrasted with data gathered during Randomized Clinical Trials (RCT). Although clinical trials are the best way to eliminate variables and accurately quantify specific effects, they have the known drawback of focusing on heterogeneous subjects in ideal settings. By eliminating the variables, they eliminate the complexities of actual experience. In addition, RWD can be gathered from high-risk subjects not suitable for clinical trials, including children and pregnant women. 

While clinical trials remain the gold standard for studying the specific effects of a medication or intervention, the progression of a disease, or the outcome of a study, RWD is an exciting new source of health information, with a variety of uses in improving health care. By comparing the results of clinical trials with the complexities of varying interventions in daily life, a more complete picture of human health emerges. 

How is Real World Data Used in Pharmaceutical Care and Research? 

When RWD is gathered and analyzed, the resulting data is referred to as “Real World Evidence” (RWE). According to the US FDA, RWE is “the clinical evidence regarding the usage and potential benefits or risks of a medical product derived from analysis of RWD.” RWE is gathered from observational studies of RWD, and can take the form of large-scale cohort or cross-sectional studies, among others. Data can be analyzed prospectively or retrospectively, and assess different aspects of health and health care. 

The most common use of RWE is as part of post-marketing treatment surveillance. Regulatory authorities already require manufacturers to collect safety information after the launch of a new drug, typically referred to as Phase IV studies. Using real-world data generates more insights and more unfiltered information about side effects, reactions, and long-term results in variable conditions, meeting the need for safety surveillance studies. 

In recent years, RWE has been used to speed up regulatory decisions regarding the approval of medical products. In 2019, the US FDA approved the use of palbociclib, a new breast cancer treatment, in men, based on RWE of off-label use. This is an ideal use case for RWE, because the incidence of breast cancer is so low in men, making clinical trials difficult. 

Finally, RWE can be used to streamline and simplify the control aspect of a clinical trial. For some studies with predictable disease progression and known treatment effects, existing RWD can be used to augment or replace control studies, reducing the amount of time and cost associated with completing a clinical trial. 

Future Implications for Real-World Evidence in the Pharmaceutical Industry

Today, the US FDA and the European Medicines Agency are in the process of creating standards for how RWE is generated and used in health care. ISPOR is also seeking to improve the standards and practice for collection and use of this data, as data collected for one purpose is not always suitable to be adapted for a different purpose. 

Working with Real World Data in the pharmaceutical industry raises the same challenges as it does in every other industry: vast amounts of data needs to be accessed, gathered, cleaned, and analyzed in order to be useful. This task not only requires professionals with experience in machine learning and data analysis, but it also requires professionals with an understanding of life sciences, study design, and regulatory affairs. People with the ability and experience to perform this complex work within the scientific and compliance framework required in pharmaceuticals and healthcare are in critical demand.

At Grapefrute, we are experts at sourcing hard-to-find talent for the life sciences and pharmaceutical industries. We know how to solve tough recruitment challenges, and have the industry expertise to find the right people for the most in-demand jobs. If you are looking for candidates to help your company grow, compete, and innovate, contact us today.