AI & ML in Clinical Trials Fundamentals, Applications, and Regulatory Aspects Training Course: Driving Innovation in How Research is Designed, Conducted and Evaluated (Nov 6, 2025) - ResearchAndMarkets.com

DUBLIN--(BUSINESS WIRE)--The "AI & ML in Clinical Trials: Fundamentals, Applications, and Regulatory Aspects Training Course (Nov 6, 2025)" training has been added to ResearchAndMarkets.com's offering.

Artificial Intelligence (AI) and Machine Learning (ML) are rapidly reshaping the clinical trials landscape, driving innovation in how research is designed, conducted and evaluated.

While these technologies hold immense promise to enhance efficiency, reduce costs, and improve outcomes, their adoption is paired with ethical concerns, prompting the development of robust regulatory frameworks to guide their responsible use. For professionals in the field, understanding the fundamentals of AI and ML and their implications is becoming increasingly essential.

This comprehensive one-day training course provides an overview of AI and ML, focusing on their applications in clinical trials and the regulatory and ethical considerations that accompany their use. Participants will explore how AI and ML are being used to optimize trial efficiency, predict patient outcomes, and support adaptive trial designs. The course will also examine the regulatory frameworks, including the EU AI Act and related regulatory initiatives, to ensure compliance and ethical use of these technologies in a highly regulated environment.

Through engaging lectures, real-world case studies, and interactive assessments, attendees will gain valuable insights into the transformative potential of AI and ML in clinical trials while understanding the challenges and responsibilities associated with their implementation. Join us to enhance your knowledge of these cutting-edge technologies and their role in advancing clinical research.

Who Should Attend:

This course is aimed at anyone working in clinical research, clinical operations, data management, regulatory and compliance, and associated functions seeking to leverage AI and ML in clinical trials. Whether you're new to AI/ML or looking to deepen your understanding, this course provides valuable insights into how these technologies are reshaping the clinical research landscape.

Benefits of attending

• Explore the fundamental concepts of AI and ML
• Learn how to address common challenges with cutting-edge solutions
• Explore real-world use cases of AI-powered tools for clinical trial optimization
• Understand the ethical and regulatory requirements essential to adopting AI in clinical settings
• Reflect on change management in people, process, and tools for implementing an AI-based tools
• Prepare for the future of clinical trials and stay ahead of industry advancements

Certifications:

• CPD: 6 hours for your records
• Certificate of completion

Key Topics Covered:

Introduction to AI and ML

• Key concepts and terminologies
• Types of machine learning
• Applications in healthcare, trends, and innovations

Applications of AI and ML in clinical trials

• Opportunities and challenges
• Real-world data analysis
• Trial design and simulation
• Patient recruitment and retention optimization
• Predictive modelling for outcomes

Applications of AI and ML in clinical trials cont'd

• Patient monitoring and safety surveillance
• Clinical data management and analysis
• Workflow optimization

Regulatory landscape for AI in clinical trials

• Overview of FDA, EMA, and other relevant agencies' positions on AI and ML
• Validation and approval processes for AI-based tools
• Requirements for data handling and reporting

Ethical aspects

• Transparency, fairness, and accountability
• Mitigating bias in AI models
• Balancing innovation with patient safety

Integration and future directions

• Steps to incorporate AI into clinical trial workflows
• Overcoming common obstacles in AI/ML adoption
• Future directions

Speakers:

Zuzanna Kwade

Agfa Healthcare

Zuzanna Kwade is Medical Affairs Manager, Agfa Healthcare. Zusanna holds a PhD in Biochemistry and has more than ten years of experience in clinical and medical research. She is the co-author of several white papers on regulatory aspects of clinical research.

Since 2016, she has been actively involved in Clinical Evaluations according to MEDDEV 2.7.1 (Rev.4) for multiple devices, including high risk hardware devices and medical software. She also represents COCIR in the European Union Task Force on clinical evaluation of software.

For more information about this training visit https://www.researchandmarkets.com/r/xgg6g

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