Accelerating patient recruitment and drug development with real world data (RWD)

The use of real-world data to enhance clinical trials and regulatory submissions is gaining more acceptance around the world. Both regulators and payers increasingly asking for real world evidence to help understand the context of new therapies and the likely clinical and economic impact.

Real-World Data (RWD) is defined as data which has been collected from a number of sources that are associated with outcomes from a diverse range of participants in a real-world setting. Analysis of RWD generates valuable insights which can improve interventional pathways and the clinical and economic impact on participants and the healthcare system. 

Potential applications for biotech’s include:

• Patient profiling and sizing (feasibility assessment)
• Patient identification and recruitment
• Protocol designs
• Reduce size and complexity of trials
• Synthetic control arm

Trial Design 

Real-World Data can be used to identify participants with unmet clinical needs and a greater chance of benefitting from new therapy. This data may help refine the trial’s inclusion/exclusion criteria to improve the capture of target patients. RWD can help identify the best clinical trial sites and enable a more streamlined recruitment process and retention. These interventions can shorten the trial length while increasing the statistical power. 

Site Selection and Patient recruitment

One of the earliest and most important decisions to be made before a clinical trial gets underway is selecting a site to conduct the trial. 

Real-World Data can be useful in selecting a clinical trial site as Sponsors and Principal Investigators can access information including diagnosis codes, laboratory tests, and histologies to assess the number of participants that can be enrolled in each potential site and locations where clinical trials can be held. 

Having access to a database of information about the patient population and studying observations made by physicians allows for patient populations to be analysed in potential clinical trial sites and to be matched based on their characteristics. Using Real-World Data in this process can assist in bringing a smaller number of participants into a work-up with an increased enrolment ratio.