Life sciences veteran Matthew Stannard describes how the industry can leverage data and analytics to identify clinical trial participants and get drugs to market more efficiently.
Have you ever bumped into the same obstacle—maybe a sharp edge or a rise in the floor—over and over again? That’s precisely what life sciences organizations have done for years when it comes to how they use data. But instead of walking away with a stubbed toe or a headache, this persistent challenge forces pharmaceutical companies to burn more time and resources to get drugs to market. Patients, meanwhile, miss out on potentially life-saving treatments.
Take it from Matthew Stannard, life sciences advisor to InterSystems. After 20 years in all corners of the life sciences space, he understands the challenges and opportunities facing drug makers. This week on Healthy Data, a podcast series by InterSystems, we speak with Matt to learn more about how life sciences organizations can leverage data, analytics, and artificial intelligence to improve their operations.
Here are a few key points from the conversation.
· Clinical trials are facing a classic case of “two ships passing in the night.” Life sciences stakeholders can’t find participants to meet enrollment goals, even as they overlook patients who need the drug in question.
· Disparate data silos are, at least in part, to blame. Access to data from many electronic health records, retrospectively and in real time, and real-world evidence can help solve life sciences’ data challenges.
· The benefits of embracing data and technology are clear: Patients survive, and life sciences companies thrive. It’s all thanks to access and efficiency.
And COVID-19 has only exacerbated efforts to connect patients with clinical trials, Matt notes. The pandemic has disrupted operations within hospitals and life sciences organizations, leaving a major backlog that threatens further delays for critical drugs.
If the need for life sciences to get creative with data was urgent before, it’s essential now. But the good news is that despite decades of data hardship, drug manufacturers have the ability to embrace tools that could usher in a new age of life sciences innovation.