Clinical Research Data Management Course

About Course

This 12-week instructor-led course provides practical, hands-on mentorship and training in clinical research data management using open-source tools. It teaches principles of data management and concepts of data science required to support clinical research projects. It focuses on the end-to-end data lifecycle – from protocol translation and CRF development to database design, validation, data quality control, monitoring, cleaning, visualizations, curation, analysis, report writing and data archival.

Participants will gain competencies in applying Good Clinical Practice (GCP), FAIR Data Principles, and Data Protection standards, with an emphasis on using REDCap for database design and R for data management and visualization.

By the end of the course, participants will be able to:

Design clinical databases in REDCap aligned with study protocols.
Develop data management plans and workflow documentation.
Conduct data validation, cleaning, and quality checks.
Analyze and visualize clinical data using R.
Generate automated reports and dashboards for study monitoring.

Apply ethical and regulatory frameworks for secure data handling.

Course Content

Foundations of Clinical Research Data Management
An introductory course covering how clinical research data is collected, managed, cleaned, and prepared for analysis while ensuring quality and regulatory compliance.

Protocol Translation and Case Report Form (CRF) Design
Focuses on translating study protocols into structured data requirements and designing clear, accurate Case Report Forms (CRFs) that support efficient and compliant data collection.

About Course

Course Content

Foundations of Clinical Research Data Management
An introductory course covering how clinical research data is collected, managed, cleaned, and prepared for analysis while ensuring quality and regulatory compliance.

Introduction to clinical data management

Introduction to clinical research

Why Data Management Matters.

Importance of data management

The Clinical Research Lifecycle

The Role of the Clinical Data Manager

Key Characteristics of High-Quality Data

Characteristics of High-Quality Data.

Data Flow in Clinical Research

Core Principles of Responsible Clinical Data Management

Emerging Trends in Clinical Data Management

Summary

Protocol Translation and Case Report Form (CRF) Design
Focuses on translating study protocols into structured data requirements and designing clear, accurate Case Report Forms (CRFs) that support efficient and compliant data collection.

Introduction to Protocol Translation and Case Report Form (CRF) Design

Understanding the Research Protocol

Translating Objectives into Data Requirements

Identifying Primary and Secondary Endpoints

Developing a Data Collection Matrix

Introduction to CRFs in Clinical Research

Designing variables, Data Elements and study design structure.

Clinical Data Documentation and Version Control Systems

Common CRF Design Mistakes

Practical Example: Protocol-to-CRF Translation

Summary

About Course

Course Content

Foundations of Clinical Research Data Management An introductory course covering how clinical research data is collected, managed, cleaned, and prepared for analysis while ensuring quality and regulatory compliance.

Protocol Translation and Case Report Form (CRF) Design Focuses on translating study protocols into structured data requirements and designing clear, accurate Case Report Forms (CRFs) that support efficient and compliant data collection.

Foundations of Clinical Research Data Management
An introductory course covering how clinical research data is collected, managed, cleaned, and prepared for analysis while ensuring quality and regulatory compliance.

Protocol Translation and Case Report Form (CRF) Design
Focuses on translating study protocols into structured data requirements and designing clear, accurate Case Report Forms (CRFs) that support efficient and compliant data collection.