Presented by
Management Forum
Application of Artificial Intelligence (AI) and Machine Learning in Clinical Trial Data Management Training Course
AI and Machine Learning are revolutionising clinical trial data management by enhancing efficiency, streamlining processes, and minimising human error. This course will be of use in both the pharmaceutical and medical device industry.
- Format: Live online
- CPD: 6 hours for your records
- Certificate of completion
Course overview
Understand the application of AI and Machine Learning in clinical trial data management to optimize efficiency, ensure compliance with ethical standards, and gain actionable insights, transforming the future of clinical trials.
In the fast-evolving landscape of clinical trials, data management remains one of the most time-consuming and error-prone aspects of the process. Current practices rely heavily on manual data ingestion, cleaning, and review, leading to delays and inaccuracies. However, Artificial Intelligence (AI) and Machine Learning (ML) offer a ground-breaking solution to these challenges, revolutionizing how clinical trial data is collected, analysed, and utilized.
This comprehensive one-day training course explores the transformative power of AI and ML in clinical trial data management. Participants will learn how these advanced technologies can streamline workflows, reduce errors, and enhance the quality of clinical trial outcomes. From automating data review processes to providing data-driven recommendations on trial design and protocol development, AI/ML tools offer immense potential to improve efficiency across all stages of trial data management.
Join us to discover how AI and ML can elevate your clinical trial data management process, ensuring higher efficiency, improved accuracy, and better patient outcomes.
This course is of our range of Medical Devices training courses - now also including Medical Devices Cyber Security training to help improve your data security.
Benefits of attending
- Explore the fundamental concepts of AI and ML.
- Gain practical knowledge of AI/ML applications in clinical trials.
- Learn how to address common data management challenges with cutting-edge solutions.
- Explore real-world use cases and demonstrations of AI-powered data management tools.
- 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 clinical data management solution
- Prepare for the future of clinical trial data management and stay ahead of industry advancements.
Who should attend?
This course is ideal for clinical trial professionals, data managers, regulatory experts, and healthcare technologists seeking to leverage AI and ML to improve data management processes. 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 trial landscape.
Please note that the course will cover clinical trials as a whole, with no particular focus on the medical device or pharmaceutical industry. However, there will be increased information and examples from the pharmaceutical industry.
This course will cover:
Importance of data management in a clinical trial
- What is clinical trial data management?
- Key objectives and components
- Impact on regulatory submissions and patient safety
- Standards and regulatory framework for CDM
- Current challenges in clinical trial data management
Overview of AI and machine learning
- What is Artificial Intelligence (AI), Machine Learning (ML), and data science
- AI vs statistics
- Core concepts of applied ML
- Types of ML
Applications of AI/ML in clinical trial data management
- Integrated study design
- Automating data entry
- AI/ML- augmented data cleaning and processing
- Medical coding
- Reconciliation
- Query generation
- Handling missing data
Advanced data analysis
- Risk data review insights, trends and patterns (anomalies, data patterns, outliers)
- Big data reviews (audit trails, Real World Evidence, eSource data)
- Predictive analytics
Optimisation of clinical trials
- Trial design and simulation
- Recruitment and retention
- Real-time monitoring and safety surveillance
- Adaptive trials
Regulatory considerations and ethical implications
- Ethical implications of AI and ML in clinical trials.
- Regulatory requirements: Compliance with FDA, EMA, and GDPR.
- Addressing transparency and biases in AI models.
Challenges, solutions and perspectives
- Overcoming common obstacles in AI/ML adoption
- Evolving role of clinical data manager
- Future directions
Zuzanna Kwade
Dedalus Healthcare
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.
NEW higher discounts for multiple bookings - bring your colleagues to make your training budget go further:
- 30% off the 2nd delegate*
- 40% off the 3rd delegate*
- 50% off the 4th delegate*
Please contact us for pricing if you are interested in booking 5 or more delegates
10 March 2025
Live online
09:00-17:00 UK (London) (UTC+00)
10:00-18:00 Paris (UTC+01)
05:00-13:00 New York (UTC-04)
Course code 15482
- GBP 649 749
- EUR 909 1,049
- USD 1,043 1,199
Until 03 Feb
- 1 day live online training
- Browser-based, no download usually required
- See presenters and interact with fellow attendees
- Download documentation and certification of completion
- Fair transfer and cancellation policy
Not ready to book yet?
for 7 days, no obligation
30 June 2025
Live online
09:00-17:00 UK (London) (UTC+01)
10:00-18:00 Paris (UTC+02)
04:00-12:00 New York (UTC-04)
Course code 15483
- GBP 649 749
- EUR 909 1,049
- USD 1,043 1,199
Until 26 May
- 1 day live online training
- Browser-based, no download usually required
- See presenters and interact with fellow attendees
- Download documentation and certification of completion
- Fair transfer and cancellation policy
Not ready to book yet?
for 7 days, no obligation
6 November 2025
Live online
09:00-17:00 UK (London) (UTC+00)
10:00-18:00 Paris (UTC+01)
04:00-12:00 New York (UTC-05)
Course code 15484
- GBP 649 749
- EUR 909 1,049
- USD 1,043 1,199
Until 02 Oct
- 1 day live online training
- Browser-based, no download usually required
- See presenters and interact with fellow attendees
- Download documentation and certification of completion
- Fair transfer and cancellation policy
Not ready to book yet?
for 7 days, no obligation
* Early booking discounts may not be combined with other discounts or offers. As such, the discounts for 2nd/3rd/4th delegates are based on the full price; and apply only when booking multiple delegates on the same date.
