Topic: Placebell©™

March 3, 2021

What if you could predict placebo responsiveness of each patient in your clinical trial? Historical strategies to address the placebo response may help but haven’t completely solved the placebo response problem. Until now. Advanced methods like AI and machine learning are uniquely poised to help scientists uncover the full spectrum of patient placebo responsiveness in a clinical trial. Learn more about this approach by attending our webinar, which explains how a solution like Placebell©™ leverages a time-tested predictive algorithm to improve clinical trial assay sensitivity and de-risk drug development.

February 21, 2020

Dr. Dominique Demolle, CEO of Tools4Patient, recently presented data at the 16th Annual Scientific Meeting of the International Society for CNS Clinical Trials and Methodology in Washington, DC. The presentation, entitled ““Modeling of Peripheral Neuropathic Pain and Osteoarthritis Placebo Response: Working Towards a Unique Model of the Placebo Response in Chronic Pain?” was authored by Tools4Patient scientist Dr. Samuel

January 20, 2020

In analgesia randomized clinical trials (RCTs), the magnitude and the variability of the placebo response negatively impacts the ability to demonstrate superiority of active compounds compared to placebo. The first objective of this analysis was to investigate parameters influencing the placebo response in PNP as a way to control for this major confounding factor.

October 15, 2018

There is substantial scientific literature describing the placebo response in pain, including characterizing the magnitude and duration of placebo response in randomized clinical trials.

September 18, 2018

While drug developers have been struggling with the placebo response for decades, Placebell©™ is the first commercially available technology that enables scientists to control for the placebo response in clinical studies. Tools4Patient (T4P) launched Placebell©™ in late 2017,

July 20, 2018

In May 2018, Tools4Patient (T4P) presented a webinar entitled “Characterization of Individual Patient Placebo Response: Impact on the Clinical Study Power”.