Reduce variability in evaluation of treatment efficacy and increase study power
No change to clinical trial design or conduct
Innovative technology for reducing risk in drug development
Placebell©™ is a platform designed to identify each clinical trial patient's potential to demonstrate a placebo response.
The approach integrates important patient personality traits (measured by our validated questionnaire) with usual demographic and medical history data to calculate a single value, the Placebell©™ Covariate, for each patient.
Including the Placebell©™ Covariate in the statistical analyses results in a substantial reduction in variability of treatment efficacy data and an increase in clinical trial power.
Placebell©™ utilizes a composite covariate approach to reduce the variance related to the placebo response, which is a main source of data variability in clinical trials. Reducing variability translates into increased clinical trial power, and ultimately improves the sponsor's ability to demonstrate statistically significant differences in outcomes between placebo and treated groups.
Increase Clinical Trial Power
All patients are administered our validated Multi-Dimensional Personality Questionnaire (MPsQ) measuring personality traits specific to the placebo response. After database lock, the Tools4Patient team utilizes the questionnaire data and other patient characteristics as inputs in our disease-specific model to calculate the Placebell Covariate – which can then be used in the statistical analysis to decrease data variability and increase study power. Models are calibrated in each disease using Tools4Patient's proprietary AI-based algorithm.
We are currently seeking co-development partnerships to develop and calibrate Placebell©™ in new indications. Placebell©™ can be applied to virtually any disease in all therapeutic areas that experience a high placebo response. These include indications in pain, neurology, psychiatry, dermatology, ophthalmology, women’s health, gastrointestinal disease, inflammation, oncology and others.
Reducing clinical data variability. Empowering better decision making. Accelerating the launch of therapeutics to market.