RWD Strategy May Increase Value of Analytics-Generated Insights | Deloitte US has been saved
By Karla Feghali, senior manager, head of ConvergeHEALTH Expert Services, and Seshamalini Srinivasan, manager and product management lead, ConvergeHEALTH Miner platform, Deloitte Consulting, LLP
Life sciences company leaders often ask us to help them strengthen their technology capabilities and operations so that they can make more effective use of real-world data (RWD). RWD is generally defined as patient data that is routinely collected from sources outside of a controlled clinical trial. Examples include electronic health records (EHRs), claims and billing information, product and disease registries, wearable and mobile devices, and other sources that can inform on health status.1
RWD is playing an increasingly important role in life sciences and health care decision-making across disease types. The value of RWD—as well as the value of the technology that can analyze the important trends/patterns it contains—has been most recently apparent in the ecosystem’s response to COVID-19. For example, RWD combined with data from clinical trials has been used to assess the impact the virus has on patients and the effectiveness of vaccines. RWD has also been used by regulators to help determine dosage timing and the need for boosters.2 In addition, RWD is being used to understand the impact of COVID-19 on treatment patterns for other therapeutic areas (TAs). Advanced artificial intelligence and machine learning (AI/ML) algorithms were used to increase the odds of vaccine-trial success by identifying the most appropriate patient populations and the best locations for trials. This helped to ensure that vaccines were made available to the public at an accelerated pace. The combination of various sources’ of RWD data on populations with COVID-19 has produced one of the largest RWD sets ever available.3
Understandably, many life sciences companies are making sizeable investments in licensing RWD to support the understanding of disease, improve clinical-trial designs, augment trials with external control arms, and to generate innovative treatments and devices. 4 What is less clear is why many of these companies appear to be more focused on licensing different types of data from different sources than first thinking about the types of analytics-generated insights they might be able to pull from the data. Setting data strategy as an afterthought rather than a prerequisite can make it difficult to demonstrate value from newly achievable analytics.
Companies that are planning to license RWD can increase its effectiveness and value by proactively developing a data strategy that clarifies the types of data they're licensing and the subsequent analyses they want to conduct. Companies should consider focusing broadly on data that generates evidence across indications, therapies, and use cases, and allows hundreds of analyses to be run. Companies might also link internal clinical-trials data with RWD to answer novel questions at an accelerated pace. Leaders of life sciences companies should consider the following questions:
More data, more availability, more potential
The quantity and types of RWD data—and the availability of that data—have expanded substantially over the last several years, offering ever-more potential for reaping value-added insights from data analysis. The types of analyses company leaders want to conduct should determine their data strategy. This can help ensure that they can cost-effectively license the mix of foundational, TA-specific, and fit-for-purpose data that best meets their needs. Here’s a brief overview of those three types of data and how they might be used:
Over time and across analyses guided by thoughtful data strategy, life sciences companies should be able to assemble a robust, cost-effective repository of RWD from multiple commercial, academic, and non-traditional sources to help enhance current offerings and enable future innovations.
1. Real-word evidence, The US Food and Drug Administration, February 1, 2022
2. Real-world evidence confirms high effectiveness of Pfizer-BioNTech COVID-19 vaccine and profound public health impact of vaccination one year after pandemic declared, Pfizer new release, March 11, 2021
3. Effectiveness of the Single-Dose Ad26.COV2. S COVID Vaccine, medRxiv. October 2020
4. External control arms and debunking real-world data myths, pharmaphorum, August 31, 2021