Data Vigilance and Validation Lessons Learned, Future Hopes for Real-World Data

Discussing the challenges that remain around RWD and RWE, the roundtable-moderated by Peter Malamis, senior director, life sciences market development at Phreesia-aimed to shine a light on what is needed to ensure that the pharma c-suite understands the potential of RWD and where it fits into an organization's overall strategy. At Thermo Fisher Scientific's PPD clinical research business, we're organized with a cross-functional RWD evaluation and implementation structure, with representatives from the corporate strategy team, along with leaders in data architecture, technology, data curation, scientific strategy, core scientific disciplines (e.g., epidemiology, biostatistics, data science), and therapeutic area expertise, among several others, that are constantly evaluating the RWD/RWE landscape. The addition of technology solutions and platform approaches to RWD, specifically those aimed at trying to achieve a 360-degree patient view, are all part of our new RWD ecosystem requiring a strong multifunctional team and evaluation structure. Going back to the original question, "How do we choose our data?" I think it's very different when a company is choosing a data set to purchase for multiple uses internally. Because a data set's not good or bad in and of itself, other than, as Dan pointed out, accuracy.