Data Management in Clinical Research
( 24 Modules )

Module #1
Introduction to Clinical Research Data Management
Overview of the importance of data management in clinical research, roles and responsibilities of data managers, and the data management lifecycle

Module #2
Clinical Research Data Types and Sources
Types of clinical research data, data sources, and data collection methods

Module #3
Regulatory Guidelines and Compliance
Overview of regulatory guidelines and standards for clinical research data management, including ICH-GCP, FDA, and HIPAA

Module #4
Data Management Plans:Development and Implementation
Creating and implementing a data management plan, including data quality, data security, and data sharing considerations

Module #5
Data Collection Tools and Technologies
Electronic data capture (EDC) systems, case report forms (CRFs), and other data collection tools and technologies

Module #6
Data Validation and Verification
Methods for validating and verifying clinical research data, including data cleaning and data quality checks

Module #7
Data Storage and Security
Data storage solutions, data security measures, and data backup and recovery procedures

Module #8
Data Visualization and Reporting
Data visualization techniques, reporting tools, and data summarization methods

Module #9
Data Quality Control and Assurance
Data quality control and assurance processes, including data monitoring and data auditing

Module #10
Data Standardization and Normalization
Data standardization and normalization techniques, including CDISC and SDTM

Module #11
Data Integration and Interoperability
Data integration and interoperability challenges, solutions, and best practices

Module #12
Data Governance and Stewardship
Data governance frameworks, data stewardship roles, and data ownership responsibilities

Module #13
Data Analytics and Biostatistics
Introduction to data analytics and biostatistics in clinical research, including statistical analysis plans and data interpretation

Module #14
Data Management for Rare Diseases and Orphan Trials
Unique challenges and considerations for data management in rare disease and orphan trials

Module #15
Data Management for Pediatric and Oncology Trials
Specialized data management considerations for pediatric and oncology trials

Module #16
Data Management for Multi-Site and Global Trials
Challenges and best practices for data management in multi-site and global clinical trials

Module #17
Risk-Based Monitoring and Data Quality Oversight
Risk-based monitoring strategies and data quality oversight processes

Module #18
Audits and Inspections:Preparation and Response
Preparing for and responding to audits and inspections, including data management documentation and SOPs

Module #19
Data Management Technology and Innovation
Emerging trends and innovations in data management technology, including artificial intelligence and machine learning

Module #20
Data Sharing and Collaboration
Data sharing best practices, data collaboration tools, and data access policies

Module #21
Data Management for Real-World Evidence and Observational Studies
Data management considerations for real-world evidence and observational studies

Module #22
Data Management for Adaptive and Bayesian Trials
Unique data management challenges and considerations for adaptive and Bayesian trials

Module #23
Data Management for Virtual and Decentralized Trials
Data management considerations for virtual and decentralized clinical trials

Module #24
Course Wrap-Up & Conclusion
Planning next steps in Data Management in Clinical Research career

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Data Management in Clinical Research ( 24 Modules )

Data Management in Clinical Research
( 24 Modules )