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Aug 2017

AI-Driven Predictive Analytics in Risk-Based Monitoring – Part II

By |2024-05-10T17:05:52+02:00August 8, 2017|AI in Clinical Trials, Blog, Neat Features|Comments Off on AI-Driven Predictive Analytics in Risk-Based Monitoring – Part II

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 [...]

Aug 2017

AI-Driven Predictive Analytics in Risk-Based Monitoring – Part I

By |2024-05-10T17:06:46+02:00August 2, 2017|AI in Clinical Trials, Blog, Neat Features|Comments Off on AI-Driven Predictive Analytics in Risk-Based Monitoring – Part I

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 [...]

Feb 2015

What is the difference between KRIs, KPIs, and KQIs in Risk-based Monitoring? Explained simply.

By |2024-06-14T17:55:22+02:00February 18, 2015|Blog|6 Comments

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.

May 2014

7 Reasons Why Clinical Trials Fail

By |2024-06-14T17:53:42+02:00May 2, 2014|Blog|4 Comments

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...

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