Designing Trials at the Speed of Innovation: How Smart Study Design Reduced Oncology Protocol Timelines by 40%
Client
A leading global pharmaceutical company conducting multiple oncology clinical trials across regions, indications, and patient cohorts.
Business Need
The client’s study design lifecycle was slow, manual, and highly variable across teams and therapeutic areas. Lack of centralized reference knowledge led to inconsistencies in study protocols, rework across functions, and prolonged approval cycles. With oncology trials already complex and time-sensitive, delays in study design created downstream impacts on site activation, patient recruitment, regulatory submissions, and overall trial timelines. The organization needed a data-driven, standardized, and collaborative approach to accelerate study design while improving protocol quality and compliance.
Solution
To overcome the bottlenecks, the client adopted our Smart Study Design solution, powered by AI and domain-specific intelligence for oncology studies. Key solution elements included:
- Historical Study Analytics for benchmarking against past protocols and outcomes.
- AI-Powered Insights to recommend parameters such as endpoints, inclusion/exclusion criteria, dosing schedules, and biomarkers.
- Oncology-specific protocol templates to standardize protocol structure and eliminate ambiguity.
- Advanced keyword search and smart filters to quickly surface comparable study elements across thousands of historical trials.
Interactive conversational interface that enabled teams to explore datasets, ask questions in natural language, and co-create study designs collaboratively.
Benefits
- 40% reduction in study design timelines, accelerating downstream trial operations.
- 25% improvement in protocol consistency, reducing rework and improving regulatory confidence.
- Optimized study parameters driven by AI insights, lowering the risk of mid-trial amendments and delays.
- Enhanced collaboration across clinical, regulatory, medical, and biostatistics teams through a unified design workspace.
- Higher probability of trial success through better-informed, data-backed protocol decisions.