At the United States Association for the Study of Pain 2025 conference, Cognivia presented compelling new data from a Phase II trial on severe acute lower back pain “A Phase 2, Randomized, Double blind, Placebo controlled, Parallel Group, Multicenter Study to Evaluate the Safety and Efficacy of SP103 5.4% in Subjects with Moderate to Severe Acute Lower Back Pain”, highlighting the impact of Placebell baseline prognostic covariates on trial efficiency and data quality
As clinical trial methodology evolves under increasing regulatory focus on covariate adjustment, Placebell offers a scientifically grounded solution. Developed originally for chronic pain, these covariates—capturing psychological traits, disease severity, and demographics—were applied to this acute pain study with striking results.
Incorporating Placebell covariates into the primary efficacy analysis led to a 34.75% increase in precision (p < 0.001) for the primary endpoint. Achieving the same statistical power without this model would have required 25 additional participants.
Key highlights from the poster:
- Highlighting transferability of Placebell from chronic to acute pain
- Patient stratification based on placebo responsiveness
- Improved interpretability and sensitivity in treatment effect estimates
These findings confirm that Placebell covariates are not only robust across indications but also provide a scalable, regulatory-aligned method for enhancing RCT design. For sponsors and CROs, this translates to higher-quality data, much higher precision of treatment effect size and chance to detect an effect without inflating sample size, and more efficient trials—without compromising scientific integrity.
To deploy Placebell technology is to apply a novel and scientifically grounded approach to one of pain research’s most persistent challenges: the placebo response. Traditional approaches often treat placebo effects as statistical noise, but Placebell accounts for them as meaningful signals. Learn more reading our eBook.