- Optimized protocol design
- Real-time Inclusion/exclusion modeling
- Adaptive design scenarios
Timely and Informed Go/No-Go Decision Making
Proof of Concept requires candidate pipeline therapies to be evaluated for safety and efficacy for a go / no-go decision in the shortest time frame possible. Advancements in statistical approaches via adaptive design and faster data processing of clinical trial information have partially contributed to faster cycle times; however, many Phase I & II studies still languish due to challenging protocol designs, including too-stringent recruitment criteria.
Fast, Evidence-Based, Protocol Design
CliniWorks‘ healthcare data analytics technologies provides research teams responsible for defining the intent-to-treat populations, and refining protocol design, with a powerful suite of tools that allow for real world evidence-based, inclusion/exclusion criteria optimization.Researchers have the ability to perform multiple protocol design simulations and scenarios on large patient population-based clinical outcomes data. Protocol inclusion and exclusion criteria that are too restrictive can be adjusted in increments, such as a specific lab test value, and run again. Valuable insights into expected recruitment rate and patient profile characteristics begin to emerge which provide for additional opportunities leading to better protocol design and reduced risk on clinical program execution.