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

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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 ensuring and unmatched data integrity and significantly reducing data management cycle times.

Why Attend This Webinar?

You will learn about the impact of DTect AI on the clinical data value chain and see a live demo Discover how DTect AI revolutionizes Clinical Operations, Data Management, Safety, and Medical Monitoring, enhancing data quality and accelerating decision-making processes. Through real-world case studies and expert insights, you’ll gain a comprehensive understanding of DTect AI’s critical role in clinical trials and how it helps organizations achieve their goals effectively.

Key Learnings:

  • Review major limitations of traditional data management and risk monitoring methods.
  • Learn how AI-powered platforms like DTect AI transform traditional data review processes, with focus on automated anomaly detection and real-time data quality monitoring.
  • Leverage AI analytics to optimize site performance metrics and protocol compliance while reducing data review cycles.
  • Harness data potential through sophisticated actionable insights that go further than basic dashboards. 
  • Explore case studies and experience a live demo showcasing how Clinical Operations teams can leverage AI-driven insights to enhance efficiency and accuracy.

What Makes DTect AI Stand Out?

  • Outperforming Traditional Methods: DTect AI uses AI to automate data reviews, integrate diverse datasets, detect anomalies in real time, and deliver actionable insights—making it a strategic enabler of clinical trial success.
  • Regulatory Compliance: Adhering to FDA and ICH guidelines, DTect AI accelerates results delivery to research teams, facilitating timely issue resolution.
  • Advanced RBQM Capabilities: Serves as a catalyst for Risk-Based Quality Management (RBQM) by identifying real-time outliers, providing prescriptive and actionable oversight of risk factors, and monitoring QTL performance through adaptive and intelligent analytics.
  • Leveraging Advanced Technologies: DTect AI integrates statistical models, AI, and machine learning algorithms to analyze collected data, ensuring consistency and avoiding biased or erroneous outcomes.

Register now to join an interactive session and empower yourself and your team for greater efficiency and success!

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Speakers

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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 Ivaturi 

Data Analytics and Engineering Leader

Jayasree has 15.6 years of experience in providing analytical solutions using business intelligence and analytical tools. Primarily focuses on understanding key analytical challenges in pharmaceutical environment and working closely with key stakeholders across clinical operations. Expertized in building advanced analytical solutions that establish insights into data, providing signals, patterns, trends, and works across different functions to break down barriers between silos while providing a data-driven integrated & holistic view to end users. 

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