While significant placebo responses rates are often noted in clinical trials for indications like pain and depression, this issue can plague drug development in any therapeutic area – particularly in diseases that rely on subjective or patient-reported outcomes as primary efficacy endpoints. Quality of life (QoL) endpoints, for example, are often used to measure therapeutic efficacy in oncology clinical trials – but also in diseases like schizophrenia, pain, heart failure, inflammatory bowel disease (IBD), allergy and pruritus.
Using Predictive Modeling to understand the impact on assay sensitivity The placebo response is a heavily studied and historically challenging phenomenon for drug developers. Strong placebo effect diminishes the ability to distinguish efficacy of an experimental drug, leading to phase II and III trial failures1– even for otherwise effective drugs. Researchers have long devised strategies
Each September, pain advocates and specialists raise awareness about issues facing the millions of people living with chronic pain. One of the most pressing? The lack of treatments available to alleviate suffering. In this blog, we look at three top challenges of getting new pain drugs to market—and offer a potential solution.
Belgian startup Tools4Patient recently presented data showing its novel technology Placebell©™ predicted placebo response in a Phase 2 randomized controlled trial (RCT) for osteoarthritis (OA). Placebell is the first robust technology using predictive modeling that is proven to reduce the impact of the placebo response in clinical trials under real-world conditions. Data from the Phase 2 RCT, “Predicting the Placebo Response in OA to Improve the Precision of the Treatment Effect Estimation,” was presented as a late-breaking abstract at the OARSI Connect Virtual World Congress on Osteoarthritis on April 29, 2021. This innovation by Tools4Patient is a major advancement for increasing clinical study success and reducing drug development costs and timelines.