Summary
This paper reviews multidimensional frameworks for rescuing underperforming oncology clinical trial sites, addressing common challenges such as inadequate recruitment and poor data quality. The authors propose integrated strategies including specialist rescue teams, enhanced staff training, centralised monitoring, and digital technologies such as real-time analytics and artificial intelligence. The analysis demonstrates that proactive optimisation can restore site performance, improve data integrity, and accelerate therapeutic delivery whilst reducing regulatory risk and trial delays.
UK applicability
The governance and operational frameworks described may have limited direct applicability to UK farming systems and soil health research, as this paper concerns oncology clinical trial administration rather than agricultural or nutritional science.
Key measures
Site performance metrics including patient recruitment rates, protocol deviation frequencies, data query rates, Good Clinical Practice (GCP) adherence, trial timelines, and cost impact
Outcomes reported
The study examined strategies for revitalising underperforming oncology clinical trial sites, measuring improvements in patient recruitment, protocol adherence, data quality, and trial efficiency following rescue interventions.
Topic tags
Dig deeper with Pulse AI.
Pulse AI has read the whole catalogue. Ask about this record, its theme, or how the findings apply to UK farming and policy — every answer cites the underlying studies.