Clinical Trials in 2026: Trends Shaping the Year Ahead

In a recent video compilation from Applied Clinical Trials, four industry leaders discussed the trends and inflection points they expect to define clinical research in 2026, spanning site operations, patient access, AI implementation, and trial design methodology.

Kevin Williams, EVP and chief strategy officer at Ledger Run, highlighted the growing complexity sponsors face when deciding how to structure their operational models. Whether through functional sourcing, CRO partnerships, or new technology systems, sponsors are increasingly bringing capabilities in house, but Williams cautioned that these decisions carry downstream consequences for sites. He pointed to switching burden as an underappreciated challenge: sites routinely navigate different systems and processes across sponsors and CROs, and operational changes that ignore this friction risk compounding it.

Liz Beatty, co-founder and chief strategy officer at Inato, addressed the tension between efficiency and access. While AI and technology are reshaping feasibility, site selection, and enrollment, she warned that concentrating trials among familiar, established sites—a common efficiency shortcut—restricts patient access and narrows trial populations. In 2026, she expects sponsors to redefine efficiency to include community site partnerships, point-of-care research integration, and outreach to underrepresented populations, arguing that access and speed are not mutually exclusive.

Angela Zubel, chief development officer at Debiopharm, framed 2026 as an implementation year—the moment when AI tools move from pilot programs into meaningful daily operations across drug development. She noted that her own organization has already made this shift, and expects the broader industry to follow.

Marc Buyse, ScD, founder and CEO of IDDI, made the case for a methodological evolution in trial design. He described generalized pairwise comparisons and the win ratio as approaches that allow multiple outcomes to be analyzed together in a single primary analysis, increasing statistical power and producing results that are more relevant to patients and scientists alike.