On-time, on-budget clinical trials—using real-time insights gleaned from healthcare, competitive, and market intelligence data
Unmet Need Analysis
Measure the level and nature of unmet need in any disease along the following domains:
- Product Need (efficacy, safety, convenience of dosing)
- Disease Seriousness (mortality and morbidity)
- Disease Cost (direct and indirect costs)
Enrollment Planning and Forecasting
- Leverage advanced predictive analytics and data visualizations to model potential scenarios and multiple cohorts
- Forecast and continuously tune enrollment completion using predictive analytics
- Track and systematically report on detailed enrollment costs for every trial
- Monitor enrollment across the entire portfolio of trials, regardless of partner or sponsor involvement
Epidemiological Studies
- Analysis of epidemiological data for specific or unusual indications, demographic factors or geographic consideration
- Customized comorbidity and risk factor analysis
- Support for orphan drug submissions
- Customized epidemiological data mining
Cost Budgeting
- Develop budget scenarios. Assess cost per patient, cost per procedure, cost per visit as well as institutional cost
- Eliminate redundant payments
Feasibility and Site Selection
- Site identification and profiling
- Patient population profiling to design and tune protocols
- Risk factors to recruitment (time and budget implications)
- Standard of care impact
- Recruitment and retention challenges
Clinical Trial Optimization
- Leverage data to gain insight into protocol design and feasibility, as well as the market and competitive dynamics that could affect trials
- Find the investigators and sites who have a track record of success and access to the right patients
- Access potential savings due to studies covered by third party insurers
Product Safety Analysis
- Early drug safety trend and adverse event signal detection
- Improved drug safety and operational effectiveness
- Proactive unstructured social data mining