There is a rapidly growing amount of information to process in clinical research. You could argue whether it adds value viewing and verifying the reliability of each single data point. Dirty data and frauds have always existed but can eventually be marginalised by responsive people and processes.
“There are always a million reasons not to do something” A great inspiring quote from Jan on an episode of The Office when Pam was making excuses not to go to Art school. A very recognisable habit, isn’t it? Talking ourselves out of [...]
The RBM software EarlyBird® obtains a powerful and flexible system for ad-hoc reporting of risk-relevant data. It can be used to explore clinical data in more detail, prepare centralized monitoring reports, and build up a risk overview across studies. An example of such a [...]
In our previous "predictive analytics in RBM" article, we started a discussion about algorithms of machine learning (ML), predictive analytics, and artificial intelligence. We also covered that a risk software needs to calculate forecasts of Key Risk Indicators (KRIs) proactively and alerts when they [...]
Predictive analytics is a very useful tool in the risk-based monitoring and overall risk-based study management. It increases the proportion of correct decisions, as the decisions start being more data-driven. It also helps to understand for a central CRA or study manager the trending [...]
Weekly RBM Feature: this is a series of articles, where we want to describe some innovative RBM features and our approach in dealing with analysis, presentation, and mitigation of risks in clinical trials. Last time we took a look at the Risk Flower chart and [...]
Weekly RBM Feature: this is a series of articles, where we want to describe some innovative RBM features and our approach in dealing with analysis, presentation, and mitigation of risks in clinical trials. To anyone “in the know” of the main purpose of the EarlyBird [...]