7 key trends in clinical trial development in 2026

Background. Clinical trials are evolving amid simultaneous protocol complexity growth, increasing data volume, rising quality requirements, and mounting pressure on research sites. Against this backdrop, digital solutions, hybrid models, artificial intelligence, real-world data, and new participant engagement formats are no longer isolated technological innovations but increasingly influence study feasibility. The ability of the research system to maintain scientific rigor, participant safety, data quality, and operational resilience while implementing new approaches becomes particularly important. For the Russian context, the development of electronic informed consent, which has received a legal basis in industry regulation, is of additional relevance.

Objective. To analyze current trends in clinical research characterizing the present stage of industry development, including technological, organizational, and patient-oriented changes.

Methods. An analytical review of current publications devoted to contemporary trends in clinical research was performed. The analysis included review and analytical materials reflecting changes in digitalization of research, artificial intelligence applications, decentralized and hybrid models, use of real-world data, patient-oriented design, site readiness, and advanced therapy development, as well as a comparison with trends described in 2023 publications as additional context for interpreting identified changes. Th e methodology included analysis of industry reports (WCG, Veeva, Signant Health), regulatory documents (EMA, FDA, Russian Ministry of Health), and peer-reviewed scientific articles.

Results. The analysis of sources identified several interrelated directions in clinical research development in 2025–2026. Artifi cial intelligence is increasingly applied in planning, site selection, document processing, data analysis, and risk-based process support. Hybrid and decentralized elements are used to improve study accessibility and reduce burden on participants and sites while maintaining data quality requirements. Real-world data, digital biomarkers, and continuous monitoring expand planning capabilities and assessment of result applicability to routine medical practice. Site readiness to rapidly adapt to new protocol requirements becomes a study sustainability factor, as protocol complexity, staffing burden, and digital system fragmentation affect timelines, data quality, and deviation risk. The patient-oriented approach transforms into a partnership model with participants, where burden reduction, clear communication, trust, and individual consideration matter. Advanced therapies create additional requirements for infrastructure, logistics, safety, and long-term follow-up. In Russia, the electronic informed consent process is emerging as a distinct area of digitalization of participant-research team interaction.

Conclusion. Current clinical research trends reflect the industry's transition to a more manageable and technologically mature model. Study quality is increasingly determined not by the mere fact of implementing digital tools, but by their connection to protocol scientific validity, site readiness, data quality, participant safety, and clear communication.

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