PRODUCTS

Business Process Automation

StudyOptimizer provides you with a consistent business process for trial enrollment. This enables a life sciences company to continually improve and optimize its enrollment processes, and standardize around best practices.

Standardized System Keeps Global Teams on the Same Page

StudyOptimizer establishes and measures all key performance indicators. A standardized approach keeps local and global teams on the same page, and web-based collaboration keeps everyone working efficiently. The result is improved transparency and better global collaboration.

Tapping into completed study data offers valuable insights into what worked best for each country. Study teams can use country screening rates and screen failure rates to plan new studies. They can also drill down into historical studies to identify top investigators and filter out under-performing sites for future trials.

Visualizations & Scenario Modeling Tools Keep Enrollment on Track

Once enrollment begins, StudyOptimizer’s visualizations and scenario modeling tools improve the predictability of trial completion dates by identifying problems before they impact the trial schedule. By modeling the best course of action, these tools help study managers take corrective actions quickly. StudyOptimizer’s visualizations go above and beyond what can be done manually or in spreadsheets. The result is study managers keep enrollment on track.

Automated Aggregation Enables Informed Decisions & Improves Efficiency

Most organizations track patient enrollment using spreadsheets, home grown systems, or commercial applications like CTMS, IVRS, or EDC. StudyOptimizer aggregates enrollment data from any of these sources and augments it with enrollment forecasts, expected milestone achievement, and alerts that help study managers make informed clinical trial enrollment decisions. Because normalized data is aggregated on a real-time basis, organizations are able use a common set of metrics to monitor enrollment performance.

 

Related Terms:
predictive analytics, clinical trial tools, enrollment modeling