Clinical Data Management is responsible for the life cycle of clinical data from collection to delivery for statistical analysis in support of regulatory activities. Clinical Data Management is primarily focusing on data flows and data integrity (i.e., data is managed the right way). Clinical Data Science broadens this focus by adding the data risk, data meaning, and value dimensions for achieving data quality (i.e., data is credible and reliable). Clinical Data Science also expands the scope of Clinical Data Management beyond the study construct by requiring the ability to generate knowledge and insights from clinical data to support other clinical research activities which require different expertise, approaches, and technologies.
COURSE CURRICULUM
- Drug Discovery and Clinical Research
- ICH GCP (Good Clinical Practice)
- 21 CFR Part 11 _ Electronic Records, Electronic Signatures
- Standard operating procedures (SOP’s)
- Protocol and Informed Consent process
- Clinical Data Management Process and Life cycle
- Data Management Plan (DMP)
- User Acceptance Testing (UAT)
- CRF Design
- Data Capture Methods
- Data Entry
- Edit Checks
- Data Validation Procedures
- Discrepancy Management
- Data Clarification Forms (DCFs)
- Database Locking and Freezing
- Data Storage & Archival
- Data Coding and Medical Dictionaries
- SAE Reconciliation
- CRF Annotation
- CDISC Standards
- AI/ML in Clinical Data Management
OTHERS
- Daily Tasks
- Certification Guidelines
- Sample Questions
- CV/Resume Preparation
- Mock Interviews
- Group Discussions
- Personality Development