Module #1 Introduction to Data Management in Clinical Trials Overview of the importance of data management in clinical trials, regulatory requirements, and best practices
Module #2 Clinical Trial Data Management Fundamentals Definition of data management, data flow, and data quality in clinical trials
Module #3 Regulatory Requirements for Data Management Overview of regulatory guidelines and standards for data management in clinical trials, including FDA, EMA, and ICH guidelines
Module #4 Data Management Planning Development of a data management plan, including data management strategy, data quality control, and data quality assurance
Module #5 Data Collection and Acquisition Overview of data collection methods, including case report forms, electronic data capture, and data import
Module #6 Data Quality Control and Assurance Methods for ensuring data quality, including data cleaning, data validation, and data verification
Module #7 Data Management Systems and Tools Overview of data management systems, including clinical trial management systems, electronic data capture systems, and data warehouses
Module #8 Data Integration and Interoperability Methods for integrating data from multiple sources, including data standardization and data harmonization
Module #9 Data Security and Confidentiality Importance of data security and confidentiality in clinical trials, including data encryption and access control
Module #10 Data Backup and Archiving Strategies for data backup and archiving, including data storage and data retrieval
Module #11 Data Quality Metrics and Reporting Overview of data quality metrics and reporting, including data quality dashboards and data quality reports
Module #12 Data Management and Analytics Overview of data analytics and visualization in clinical trials, including data mining and statistical analysis
Module #13 Risk-Based Monitoring and Data Quality Overview of risk-based monitoring and its impact on data quality, including targeted source data verification
Module #14 eSource Data and Direct Data Capture Overview of eSource data and direct data capture, including electronic health records and wearables
Module #15 Real-World Data and Real-World Evidence Overview of real-world data and real-world evidence, including claims data and patient-generated data
Module #16 Data Management in Phase I and Early Phase Trials Unique challenges and considerations for data management in phase I and early phase trials
Module #17 Data Management in Late Phase and Observational Trials Unique challenges and considerations for data management in late phase and observational trials
Module #18 Data Management in Pediatric and Rare Disease Trials Unique challenges and considerations for data management in pediatric and rare disease trials
Module #19 Data Management in Global Clinical Trials Unique challenges and considerations for data management in global clinical trials, including cultural and language differences
Module #20 Data Management Audits and Inspections Preparation for data management audits and inspections, including data quality reviews and data validity checks
Module #21 Data Management and the Data Managers Role Overview of the data managers role and responsibilities in clinical trials, including data management strategy and data quality oversight
Module #22 Data Management and the Clinical Trial Team Overview of the clinical trial teams role in data management, including data management collaboration and communication
Module #23 Data Management Innovations and Trends Overview of innovations and trends in data management, including artificial intelligence, machine learning, and blockchain
Module #24 Data Management Best Practices and Standards Overview of best practices and standards for data management in clinical trials, including CDISC and CDASH
Module #25 Course Wrap-Up & Conclusion Planning next steps in Data Management in Clinical Trials career
