In our previous "AI-driven predictive analytics in RBM" article, we started a discussion about algorithms of machine learning (ML), predictive analytics, and artificial intelligence (AI). We also covered that a risk software needs to calculate forecasts of Key Risk Indicators (KRIs) proactively and alerts [...]
AI-driven Predictive Analytics is a very useful tool in risk-based monitoring and overall risk-based study management. It increases the proportion of correct decisions once the decisions start to become more data-driven. It also helps to understand for a central CRA or study manager the [...]
How to avoid audit findings in a Risk-based Quality Management (RBQM) and risk management environment? What are auditors looking for?
Risk-based Monitoring jargon doesn’t require rocket science. You don’t have to be a statistician to analyse and interpret KPIs, KRIs and KQIs. We explain their meaning and differences through simple examples, so you can optimise key performance of your clinical trials.
In October 2014 at the Risk-based Monitoring conference in Copenhagen the Senior Director QA Operations of Janssen, Jan Van Parijs said: "Industry is historically heavily regulated, so as an industry we are kind of used to the fact that the authorities provide a set [...]
What feeling do you have, when starting a new clinical trial? Do you hope all past problems will stay in the past and that everything will be better from now on? Does it surprise you that the skill set of project managers seems to be a critical source of error according to industry experts? Then continue reading...
