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
Placebo response is one of the biggest threats to clinical data analysis– especially when left unchecked. In this blog, we review the top three risks trial scientists must address (and how to address them).
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.
Tools4Patient presented data at the MDS Congress 2021 that predicted the placebo response in Parkinson’s disease (PD) in a multi-center, multi-national clinical study.
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.