| Attribute | Detail |
|---|---|
| Format | Online (e-LMS) |
| Level | Intermediate |
| Duration | 3 Months |
| Certification | e-Certification + e-Marksheet |
| Fee | ₹2499 / $59 |
| Tools | R SAS SPSS Electronic Data Capture (EDC) Systems Database Management Tools |
About the Mastering Data Management and Analysis: From Collection to Insights Course
Data Management in Clinical Research involves the systematic collection, processing, and analysis of clinical trial data to ensure accuracy, integrity, and compliance with regulatory standards.
This comprehensive 12-week program equips learners with end-to-end expertise in clinical data management, from designing Case Report Forms (CRFs) and implementing Electronic Data Capture (EDC) systems to performing advanced statistical analysis and generating evidence-based insights. Participants will master data quality assurance, database design, query management, and data visualization while gaining hands-on experience with industry-standard statistical software including R, SAS, and SPSS.
Program Highlights
• Comprehensive coverage of Mastering Data Management and Analysis from fundamentals to advanced applications
• Hands-on projects and real-world case studies in Clinical Research
• Expert-curated curriculum aligned with current industry standards
• Access to recorded lectures and e-LMS platform for flexible, self-paced learning
• e-Certification and e-Marksheet upon successful completion
• Dedicated mentor support and interactive doubt-clearing sessions
• Practical experience with tools: R, SAS, SPSS, Electronic Data Capture (EDC) Systems
• Career-oriented training for academic and professional growth in Clinical Research
Course Curriculum
Module 1: Foundations of Clinical Data Management
- Understand data management processes, roles, and regulatory frameworks in clinical research
- Apply principles of data quality, integrity, and security to protect sensitive clinical information
- Evaluate the importance of standardized data management practices for reliable research outcomes
Module 2: Data Collection and CRF Design
- Design effective data collection tools and Case Report Forms (CRFs) for clinical trials
- Implement data validation protocols and quality control strategies to ensure accurate capture
- Optimize CRF structures to minimize errors and streamline downstream data processing
Module 3: Electronic Data Capture (EDC) Systems
- Explore EDC system architecture and advantages over traditional paper-based data collection
- Configure and deploy EDC platforms for efficient clinical trial data management
- Integrate EDC workflows with existing clinical research infrastructure and processes
Module 4: Data Entry, Cleaning, and Validation
- Execute systematic data entry processes with rigorous quality control checkpoints
- Apply data cleaning techniques to identify and resolve inconsistencies, duplicates, and outliers
- Validate clinical research data against predefined rules to ensure regulatory compliance
Module 5: Database Design and Query Management
- Apply relational database design principles to organize complex clinical datasets efficiently
- Generate, track, and resolve data queries to maintain database accuracy and completeness
- Optimize database structures for rapid retrieval, reporting, and audit trail maintenance
Module 6: Data Monitoring and Quality Assurance
- Implement risk-based monitoring strategies to prioritize data quality oversight efforts
- Conduct source data verification to confirm accuracy and traceability of clinical records
- Establish quality assurance frameworks that align with ICH-GCP and regulatory guidelines
Module 7: Statistical Analysis Planning and Methods
- Develop comprehensive data analysis plans with appropriate statistical methodologies
- Calculate sample sizes and perform power analyses to ensure study statistical rigor
- Select and justify descriptive and inferential statistical techniques for diverse research questions
Tools, Techniques, or Platforms Covered
R SAS SPSS Electronic Data Capture (EDC) Systems Database Management Tools
Real-World Applications
- Apply Mastering Data Management and Analysis skills directly to academic research, thesis work, and publications
- Build a professional portfolio showcasing practical Clinical Research competencies
- Solve industry-relevant problems using Mastering Data Management and Analysis methodologies and tools
- Contribute to open-source projects and collaborative research in Clinical Research
- Prepare for competitive examinations, interviews, and professional certifications in Clinical Research
Who Should Attend & Prerequisites
- Industry-recognized e-Certification + e-Marksheet from NSTC
- Hands-on training with practical projects and industrial datasets
- Dedicated expert mentorship and doubt resolution
Certification
