Clinical trials are crucial for drug development but often face delays due to poor site selection, which can lead to protocol violations, poor data quality, and increased costs. Ninety percent of clinical trials fail to meet their timelines, and issues like inadequate staffing and patient recruitment are significant challenges. Traditional site selection methods are inefficient, and the COVID-19 pandemic has further complicated the process. Data-driven insights can optimize site selection by evaluating current data on patient populations, investigators, and site capabilities.
Most AI pilots in drug development fail not from poor technology but from lack of strategic prioritization, organizational readiness, integrated data infrastructure, and disciplined governance, making success dependent on business discipline rather than technical capability.
In a video interview prior to the 2026 DPHARM conference, Andrea Valente, CEO of uMotif, explains why the real technology challenge isn't usability alone—it's making it easier for patients and sites to interact more effectively with each other.
In today's ACT Brief, we examine what patient-site relationships need most at DPHARM, how platform-based AI scales across workflows, and FDA's approval of a gene therapy for a rare childhood syndrome.
In a video interview prior to the 2026 DPHARM conference, Andrea Valente, CEO of uMotif, shares what she expects to be at the center of the conversation—from building trust between patients and sites to where AI may and may not have a role in that relationship.
A platform-based approach connects AI across workflows, data and governance, helping life sciences organizations move from isolated wins to real scale.
In today's ACT Brief, we examine what genuine patient voice requires beyond buzzwords, why AI's next bottleneck is system integration not models, and how regulators across three jurisdictions are formalizing patient input requirements.
The clinical research industry talks about patient-centeredness constantly but embeds it too late, too narrowly, and without clear ownership, and the cost shows up in enrollment failures, protocol deviations, and outcomes that don't reflect what patients actually care about.
