AI in Clinical Trials

Starting from predictive analytics introduced in 2017, we have continually expanded our AI capabilities. By 2020, we were leveraging Machine Learning for predictive analytics across all clinical research metrics, providing precise and comprehensive insights.

In 2023, we introduced “Ask AI” for clinical risk assessment and AI-augmented regulatory inspections, enabling targeted and efficient risk assessments and regulatory preparations.

In 2024, we launched AI-augmented clinical Due Diligence, further enhancing our suite of AI-driven solutions. This progress has been recognized with Microsoft Healthcare AI Certification in 2025, achieved after a rigorous independent audit, underscoring our commitment to ethical, validated AI in clinical trials.

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 [...]

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