Enabling More Meaningful Evidence in Pain Studies
Pain trials fail at a striking rate. Fewer than 1% of new pain therapies advance from Phase I to FDA approval, versus roughly 6.5% across novel drugs overall. Why? Because trials still depend on infrequent, clinic-based scales that miss between-visit fluctuation and real-world function. Moreover, adding sample size has not fixed the problem.
This Evidence Snapshot makes the case for a different approach to pain measurement: frequent, at-home capture that pairs PROs with objective signals of activity, mobility, and physiology.
Inside the Pain Measurement Snapshot
- Why legacy pain scales like BPI, NRS-11, and VAS provide limited insight between clinic visits
- Two case studies in brief: recovery trajectories after hip replacement, and sickle cell pain episodes interpreted against individual baseline
- What context-driven pain measurement means for competitive advantage in pain programs
Download the snapshot, or contact Koneksa to discuss how this approach could be configured for your study.
Download the fact sheet
Related Resources

Human-in-the-Loop: Why Experts Matter More in the Age of AI
Human-in-the-Loop: Why Experts Matter More in the Age of AI

Meet Lodestarâ„¢: Your North Star for Regulatory Submissions
Meet Lodestarâ„¢: Your North Star for Regulatory Submissions

Cardiovascular Measurement