Data Management in Clinical Trials
What you'll learn
- Understand the fundamental principles and best practices of clinical data management in clinical trials.
- Use key tools and technologies such as electronic data capture (EDC) systems, while adhering to regulatory standards.
- Design clinical trial databases, ensure data quality, and apply security measures to protect patient privacy and confidentiality.
- Implement data standards such as CDISC (SDTM and ADaM) in clinical trials, facilitating data integration and analysis.
- Apply techniques for data validation, cleaning, and analysis, and generate statistical reports in compliance with regulations.
- Prepare and submit data to regulatory authorities, ensuring adherence to international requirements
- Explore emerging technologies like artificial intelligence, machine learning, and blockchain to enhance efficiency and security in clinical data management.
Requirements
- Not required
Description
This 10-module course provides a thorough and comprehensive exploration of data management in clinical trials, covering both foundational principles and cutting-edge developments in the field. Participants will gain in-depth knowledge about how data is organized, structured, and managed across all phases of a clinical trial, ensuring that the data maintains its quality, integrity, and security throughout the entire process. The course delves into essential topics such as data collection methodologies, the utilization of electronic data capture (EDC) systems, and the adherence to global standards like CDISC (Clinical Data Interchange Standards Consortium). It also addresses critical privacy regulations, including GDPR and HIPAA, ensuring that participants understand the legal and ethical aspects of handling clinical data.
Further, the course highlights the processes involved in preparing clinical trial data for submission to regulatory bodies, such as the FDA and EMA, focusing on the importance of meeting specific technical and formatting requirements. In addition to these core components, the course examines recent innovations in the field, such as the integration of artificial intelligence, blockchain technologies, and real-world data (RWD) in clinical trials. These modules provide participants with a forward-thinking perspective, equipping them with the tools and knowledge to navigate the evolving landscape of clinical data management.
Who this course is for:
- Professionals in the pharmaceutical and biotechnology industries looking to enhance their knowledge of data management in clinical trials.
- Clinical research coordinators, monitors, biostatisticians, and data managers involved in clinical trials.
- Personnel from contract research organizations (CROs) and clinical trial sponsors.
- Students and recent graduates in fields such as health sciences, biomedicine, statistics, and technology.
- Anyone interested in understanding how data is managed within the context of clinical trials, including regulatory and technological aspects.
Instructor
- 4.2 Instructor Rating
- 208 Reviews
- 968 Students
- 10 Courses
Clinical Project Manager, Independent Expert (European Commission), R&D Technical Expert, Consultant in clinical research, medical writer and professor of the Master in Clinical Trials at the University of Seville.
Graduate in Pharmacy, I have studied a Master in Clinical Trials at the University of Seville, a Master in Project Management at the Complutense University of Madrid and an Executive MBA in Marketing. I also hold the title of Internal Quality Auditor (ISO 19011 Update: 2012).
I have participated in studies of Advanced Therapies, Cardio-metabolism (more specifically Heart Failure), Neuroscience (Multiple Sclerosis), Pain, Oncology, Hematology, COVID-19 and medical devices.