Implementing Diversity, Equity, and Inclusion in Drug Development
Jennifer Kim, PhD, assistant research professor, Tufts School of Medicine, Tufts Center for the Study of Drug Development, discusses barriers to participation for underrepresented populations in clinical trials and how Tufts is conducting research to better understand their nature.
Decentralized trial models have demonstrated real gains in enrollment performance and patient access, but operational switching costs, fragmented technology stacks, and unresolved gaps in the patient-site relationship raise a question the industry has been slow to confront directly.
In a video interview prior to the 2026 DPHARM conference, Andrea Valente, CEO of uMotif, explains why truly understanding the patient journey from beginning to end—and building that understanding into both study design and data collection tools—remains one of the industry's most important unfinished tasks.
In today's ACT Brief, we examine technology's real role in patient-site collaboration, why AI pilot failures stem from organization not innovation, and Novo's weight-loss drug results in competitive comparison.
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.
