Course overview
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.
CPD Hours: 6
Course Content
- Day 1
- Introduction to AI and ML
- Applications of AI and ML in clinical trials
- Applications of AI and ML in clinical trials cont'd
- Regulatory landscape for AI in clinical trials
- Ethical aspects
- Integration and future directions
Speakers
Zuzanna Kwade
Zuzanna Kwade is Software Clinical Evaluation Lead at Dedalus Healthcare. Zuzanna holds a PhD in Biochemistry and has 15 years of experience in clinical and medical research. She is the co-author of several white papers on regulatory aspects of clinical research and clinical evaluation.
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 represented COCIR in the European Union Task Force on clinical evaluation of software and co-authored MDCG2020-1 guidance on clinical evaluation of MDSW.
