Impact of globalization on study complexity and cycle times

A dedicated study startup system integrated with other eClinical technologies which streamlines bottlenecks allowing stakeholders to better adhere to established timelines and budgets, cutting runaway costs and speeding the delivery of life saving medicines to those in need is essential.

Globalization has an obvious impact on organizational structure of clinical operations teams. Do centralized groups outperform non-dedicated groups? A comprehensive study conducted by Tufts Center for the Study of Drug Development (CSDD), Start-up Time And Readiness Tracking (START) II, concluded that there was no conclusive evidence that centralizing the function of site identification through to activation achieved significant improvements in terms of cycle time reductions. Irrespective of organizational structure both groups face similar challenges and see the same opportunities for improvement.

But what do the industry metrics have to say about cycle time performance of multi-country vs. single country studies? And economies of scale in clinical trials?

Key takeaways from the research:

  • Irrespective of the reasons driving globalization of studies, multi-country studies regardless of geographic region were found to have longer cycle times than single country studies. 
  • As organizations scale the number of concurrent global studies, there is a gradual increase in overall cycle times, however cycle times drop for studies spanning 20+ countries.
  • Conducting clinical trials in places with unfamiliar regulatory pathways, cultural and language differences, and limited infrastructure is highlighting the value of technology that streamlines key bottlenecks, allowing stakeholders to better adhere to established timelines and budgets.
Read Research Report
Image

Protocol design, scope, and complexity have steadily increased, and this trend will continue—and likely accelerate—as pharmaceutical and biotechnology companies target more difficult-to-treat and rare diseases, enroll more stratified patient populations, and collect higher volume and more diverse data.

-Ken Getz, Associate Professor and Director of Sponsored Research at Tufts CSDD

Oracle for Health Sciences.