Clinical Trials Are The Global Biopharma Industry's Biggest Headache

An estimated 90% of drugs fail during clinical development, with oncology failures alone costing the industry around $60 billion annually. While efficacy and safety contribute to these losses, up to half are driven by operational and strategic shortcomings. The traditional clinical trial model has changed little over the decades, remaining heavily manual, site-centric, and difficult to scale. Patients face increasing burdens from frequent site visits, complex consent processes, and fragmented experiences, leading to lower participation and higher dropout rates. At the same time, trial data is often siloed across multiple systems and vendors, limiting real-time visibility and integrated decision-making.

In response, a growing number of organizations are rethinking clinical trials through technology-enabled approaches. Advances such as AI, automation, decentralized trial models, digital biomarkers, and modern data strategies are being applied across the development lifecycle. These innovations aim to reduce risk, improve efficiency, enhance patient engagement, and enable more responsive, data-driven trial execution.