Artificial intelligence (AI) is transforming the future of drug discovery. Accelerated computing with AI has launched an entirely new paradigm that is streamlining the investigation, assessment, and creation of new drugs and therapies. These capabilities can be applied to evidence-based treatments, disease prediction, and prevention, bringing tailored therapies into widespread use. However, the exponential growth of life sciences data has put pressure on organizations to evolve. By 2025, data volumes are expected to reach 200 zettabytes. Although this data holds the potential to enable the next scientific breakthrough, issues including computational bottlenecks, limited access to mission-critical information, and poor predictive validity are major roadblocks on the path to discovery.