In biopharmaceutical development, clinical trials generate vast amounts of data from various experimental sources and methods. The ability to effectively collect, integrate, and interpret this data in a meaningful way can be a powerful tool for steering research efforts and expediting the regulatory approval process, ultimately reducing costs. But when that data is fragmented across systems, scientific organizations can experience workflow inefficiencies, compliance hurdles, and limited insight.
In this whitepaper from Sapio Sciences, they share how you can overcome the biopharma R&D bottlenecks associated with fragmented data, poor adaptability, and limited collaboration, and the role a next-generation, AI-enhanced lab informatics platform can play.