Webinar

4 Ways AI Transforms Clinical Operations: From Data Oversight to Risk Management

Discover how AI-powered integrated data review and risk-based quality management improve data oversight, site performance, and clinical trial decision-making.

February 19, 2025 On-Demand

Webinar graphic for 4 Ways AI Transforms Clinical Operations featuring clinical data and analytics experts

About this webinar

Clinical Operations teams face mounting pressure to manage growing data complexity, ensure regulatory compliance, and mitigate risks—all while meeting tight timelines. Traditional methods often lead to inefficiencies, fragmented oversight, and delayed insights.

In this exclusive webinar, discover how DTect AI, an innovative AI-powered platform, helps life sciences organizations optimize clinical trial data quality management. DTect AI transforms Integrated Data Review (IDR) and Risk-Based Quality Management (RBQM) processes, supporting stronger data integrity and significantly reducing data management cycle times.

See how AI can strengthen Clinical Operations, Data Management, Safety, and Medical Monitoring through real-world examples, expert insights, and a practical platform demonstration.

Key takeaways

Review major limitations of traditional data management and risk monitoring methods.
Learn how AI-powered platforms transform data review through automated anomaly detection and real-time data quality monitoring.
Use AI analytics to optimize site performance metrics and protocol compliance while reducing data review cycles.
Turn complex clinical data into sophisticated, actionable insights that go beyond basic dashboards.
Explore case studies and a practical demonstration of AI-driven clinical operations oversight.

What makes DTect AI stand out

Automated data review across diverse datasets, with real-time anomaly detection and actionable insights.
Support for FDA and ICH-aligned clinical data oversight and timely issue resolution.
Advanced RBQM capabilities for real-time outlier detection, risk-factor oversight, and QTL monitoring.
Statistical models, AI, and machine learning working together to improve consistency and data quality.

Watch On-Demand

Get instant access to practical insights on using AI to strengthen clinical data oversight, manage risk, and accelerate decisions.

Speakers

Matt Callahan

Sr. Principal Clinical Data Scientist & Tech-Lead Solution Owner

Matt Callahan, a seasoned Sr. Principal Clinical Data Scientist with over 15 years of experience, specializes in advancing pharmacovigilance, patient safety, and risk-based monitoring (RBM) through innovative clinical analytics and Data Science-as-a-Service (DSaaS) tools. At MaxisIT, he supports neurodegenerative disease, oncology, and immuno-oncology programs across Phase I–III trials, driving solutions that enhance data quality, streamline workflows, and empower data-driven decisions. With expertise in computational biology, biomedical science, biostatistics, and project management, Matt is dedicated to delivering impactful informatics solutions that optimize clinical operations.

Jayasree Iyaturi

Data Analytics and Engineering Leader

Jayasree brings 15 years of experience of using business intelligence and analytical tools to provide analytical solutions. At MaxisIT, Jayasree focuses on understanding key analytical challenges in pharmaceutical environment and works closely with key stakeholders across clinical operations. Jayasree has a knack for turning data into insights, and discovering signals, patterns, and trends across different functions. One of her main objectives is to provide end users with data-driven holistic views through the MaxisIT platform.