Technical poster submitted to the BIO-IT World and presented on May 3rd 2022. The implementation of an optimized data management pipeline might require multiple underlying technical solutions that should integrate perfectly one with another. It can be complicated to find its own path among off-the-shelf solutions, internal developments or a mix of both to achieve
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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).
In this article, we will first discuss the rise of DCTs, empowered by technology like ePRO in clinical trials. Then, we will review how related technology can help mitigate the risks DCTs may pose to study data.
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.
Placebo response is a major source of noise in trial data analysis, muddying the results and making it more difficult to detect true treatment effect. We know that it’s a pressing problem for clinical trials that needs solving, but where does it come from in the first place? Patient psychology, expectations and baseline severity of the disease play a significant part of a patient’s placebo responsiveness.
The main objective of most clinical trials is to evaluate efficacy and safety of an experimental treatment. To do this, statisticians compare the response of the drug-treated group(s) of patients to the response of the placebo-treated group.