Clinical Data Management Training Program: Basic to Advanced With Hands-on Experience + 1 & 3 Months Project

COURSE CIRCULUM

Week 1: Introduction to Clinical Data Management

Day 1: Overview of Clinical Data Management: Definition, Scope, and Importance
Day 2: The Clinical Trial Process: Phases and Regulatory Guidelines
Day 3: Types of Clinical Trials and Stakeholders in CDM
Day 4: Roles and Responsibilities of a CDM Professional
Day 5: Introduction to Clinical Data: Types, Sources, and Formats
Test/Quiz/ Assignment

Week 2: Regulatory Frameworks and Standards

Day 6: Regulatory Frameworks: ICH GCP, 21 CFR Part 11, GDPR, ISO standards
Day 7: Career Opportunities in CDM: Roles, Skills, and Pathways
Day 8: Introduction to CDASH and SDTM Standards
Day 9: Metadata Management in CDM
Day 10: Overview of Clinical Data Management Systems (CDMS)
Test/Quiz/ Assignment

Week 3: Data Integrity and EDC Systems

Day 11: Introduction to EDC Systems: Features and Benefits
Day 12: ALCOA+ Framework for Data Integrity, Data Quality Metrics and Their Importance
Day 13: Validation and Verification in CDM
Day 14: SAS Programming
Day 15: SAS Programming & Introduction to SAS Studio
Test/Quiz/ Assignment

Week 4: Practical Use of EDC Tools

Day 16: Introduction to REDCap
Day 17: Introduction to Medidata Rave & Open Clinica
Day 18: Introduction to Castor
Day 19: Case Report Forms (CRFs): Design and Customization
Day 20: Data Entry in Castor
Test/Quiz/ Assignment

Week 5: Core Data Operations in CDM

Day 21: Managing Source Data
Day 22: Query Management in Practice
Day 23: Lock and Unlock Procedures
Day 24: Tips for Data Accuracy
Day 25: Data Cleaning and Validation
Test/Quiz/ Assignment

Week 6: Safety and Study Setup

Day 26: SAE Reconciliation and Safety Data Management
Day 27: Timeline and Deliverable Management
Day 28: Practical on Castor
Day 29: Handling Data Discrepancies
Day 30: Regulatory Updates and Their CDM Impact
Test/Quiz/ Assignment

Need to have (Day 1 - Day 30) Assessment test

7: Advanced Practical Training

Day 31: Query Resolution and Reporting with practical
Day 32: Data Migration Strategies
Day 33: Working with CROs and Sponsors
Day 34: Vendor Management
Day 35: Introduction to Veeva Vault & Configuring a Study in Veeva Vault
Test/Quiz/ Assignment

8: Hands-on CDM Execution
Day 36: Practical: CRF Design and Deployment
Day 37: Practical: Data Entry and Validation
Day 38: Practical: Query Management
Day 39: Practical: Reports and Dashboards
Day 40: Practical: Audit Trails and Compliance
Test/Quiz/ Assignment

9: Mid-study Adaptation and Innovation

Day 41: Handling Mid-Study Changes
Day 42: Emerging Trends: AI, ML, Decentralized Trials
Day 43: Monitoring in EDC
Day 44: eConsent for Investigator Role
Day 45: Types of Recruitment in Clinical Trials
Test/Quiz/ Assignment

10: Detailed EDC
Day 46: Navigating Across Studies in EDC
Day 47: Audit Trails and Reporting
Day 48: Participant Enrollment, Data Entry, and Responding to Queries
Day 49: Performing eSignatures in EDC
Day 50: Practical session on eSignatures in EDC
Test/Quiz/ Assignment

11: Deep Dive and Professional Integration

Day 51: Freelancing in CDM
Day 52: Career Paths: Regulatory Affairs & Pharmacovigilance
Day 53: Clinical Research Coordinator and CRA Roles
Day 54: Data Manager Responsibilities
Day 55: Clinical Operations & Project Coordination
Test/Quiz/ Assignment

12: EDC System Mastery
Day 56: Creating Studies in EDC
Day 57: Monitoring and Audit in EDC
Day 58: User Role Management
Day 59: Data Extraction and Study Dashboards
Day 60: Troubleshooting and Compliance
Test/Quiz/ Assignment

Midterm Assessment (Day 31 - Day 60)

13: Roles and Responsibilities in CDM

Day 61: Data Manager Role and Responsibilities
Day 62: Data Monitoring Processes in Clinical Trials
Day 63: Administrator Role in Clinical Data Management
Day 64: Clinical Research Associate Role
Day 65: Career Mapping and Industry Readiness
Day 66: Investigator Role in EDC
Day 67: Clinical Research Coordinator Role
Test/Quiz/ Assignment

Week 14: Practical Implementation and Study Management

Day 68: Understanding Study Structures in EDC
Day 69: Creating Studies in EDC
Day 70: Managing Studies in EDC
Day 71: Adding Participants in EDC
Day 71: Monitoring Data in EDC
Day 72: User Roles and Permission Management in EDC
Day 73: Dashboard Updates and Study Monitoring in EDC
Day 74: Filling Study Forms in EDC
Test/Quiz/ Assignment

Week 15: Advanced CDM Concepts and Digital Transformation

Day 75: Skills Required for a CDM Professional
Day 76: eConsent and Its Role in Clinical Trials
Day 77: Decentralization and Remote Trials
Day 78: LinkedIn Profile Optimization for CDM Professionals
Day 79: Types of Documents Produced in Clinical Trials (Part 1)
Day 80: Types of Documents Produced in Clinical Trials (Part 2)
Test/Quiz/ Assignment

Week 16: PROJECT: Hands-on experience in building study

Day 81: Project Discussion
Day 82: Project topic distribution
Day 83: Overview of project

Week 17–20: Project work & Mock Interview

Day 84 onwards: Project work completion by learners and grading by expert
Mock Interview Sessions for learners

Clinical Data Management Project Work

Tool Used: Open Clinica & Castor EDC (All the projects can be executed using Castor EDC & OpenClinica, choice will be given to students to select the tool).

• Open Clinica: Its a free downloadable version available for researchers. One can download the latest release of OpenClinica Community Edition from the OpenClinica website without any cost.

• Castor EDC: Castor EDC is available online. Students can use and submit the project works.

• SAS: SAS studio “SAS on demand for academics” offers a free platform to learn and explore SAS programming. Students can register with their credentials and can use it. It offers a lifetime free access.

1. Basic CRF design and study setup in the EDC tool
   Objective: Learn basic navigation and features, create a simple study and CRF with events like screening and follow-up
   Deliverables: CRF form file, short report on what was built and tested
   Project Duration: 1 month

2. Creating a CRF with conditional fields in any EDC tool
   Objective: Learn to show/hide fields based on responses, design CRF for adverse events where certain fields appear only if “AE occurred = Yes.”
   Deliverables: Conditional logic described in CRF, short note on how logic was applied
   Project Duration: 1 month

3. Role-based access control and user Management in any EDC tool
   Objective: Understand various stakeholder roles in a Clinical trial, analyze how roles and permissions are managed
   Deliverables: Use matrix table roles vs. responsibility, brief justification about access control, and explanation about responsibilities
   Project Duration: 1 month

4. Design a Case Report Form for Adverse Events using EDC tool
   Identify the essential items or fields required for an adverse event
   Project Duration: 1 month

5. DBL planning and execution
   Roles and responsibilities of DM during the DBL and the necessary checklist
   Project Duration: 1 month

6. Data Management Plan using DMP tool
   Using the DMP tool, create a simple and a research-based DMP
   Project Duration: 1 month

7. Create a Data Flow diagram of Data flow in the EDC
   Objective: Create a simple flow diagram to include the process of Data management flow
   Project Duration: 1 month

8. Create a CRF for Diabetes study in children in the EDC
   Study Design, Inclusion and exclusion criteria required, Basic CRF with Demographics, Inclusion, and exclusion criteria
   Project Duration: 1 month

9. Create a 50 no’s patient list using the Demographics dataset for any study of choice
   Objectives: Use any EDC tool and create a patient list
   Deliverables: Study design, Demographics dataset, patient list
   Project Duration: 1 month

10. Draft the importance of data normalization using a dataset and Keys
    Objectives: Dataset, Normalised dataset using keys
    Deliverables: Normalised dataset
    Project Duration: 1 month

11. Create a Study design, CRF form(using EDC platform), and a Dataset with at least 10 variables for a dataset Adverse Event, Concomitant Medications, and Patient History
    Objectives: Understanding concepts of SAS programming and the Adverse Event Dataset. Population size of 50 participants, age between 25-55. Follow SDTM
    Deliverables: Give a brief Study design and variables, justifying the variables, also add concomitant medications and Patient History
    Project Duration: 3 month

12. Create a CRF using EDC tool for Dental caries in children (50 participants), Create a patient list and generate patient IDs in EDC tool, datasets for DM, Patient history, Screening and study plan
    Objectives: CRF for Dental Caries, To understand EDC tool and SAS programming
    Deliverables: CRF for the study using 50 participants, Patient list, Data sets creation
    Project Duration: 3 month

13. Draft a Study Design for an Oncology study, create CRF using EDC tool, Patient list, Demographics, Adverse Events, and generate print report and summarize using Proc Print, Proc Stat, Proc Graph.
    Objectives: Use EDC tools and SAS programming in creating Study designs and reports
    Deliverables: Study design, CRF, datasets for AE and DM. Reports using Stat and Graph
    Project Duration: 3 month

14. Draft a simple DMP with all necessary basic requirements, emphasising their importance with justification. Create user roles in any EDC tool. Create datasets and draft an appropriate study design.
    Objectives: DMP overall understanding, study design, datasets
    Deliverables: DMP document with presentation. Study design and datasets creation using SAS programming
    Project Duration: 3 month

15. Draft a complete Study design and select the variables for the datasets: Demographics, Inclusion, exclusion criteria, patient history, Concomitant medications, and screening criteria.
    Objectives: Understand EDC tools, SDTM, and Domains
    Deliverables: Study design, Datasets
    Project Duration: 3 month

16. Create a CRF form(using EDC platform), a Dataset with at least 10 variables for Adverse Event, Concomitant Medications, and Patient History, including Inclusion and Exclusion
    Objectives: Understanding concepts of SAS programming and the Adverse Event Dataset. Population size of 50 participants, age between 25-55, Along with medication details. Follow SDTM
    Deliverables: Give a brief Study design and variables, justifying the variables, also add concomitant medications and Patient History
    Project Duration: 3 months

17. Draft a complete Study design for Diabetes in young children using real world data and select the variables for the datasets Demographics, Inclusion, exclusion criteria, patient history, Concomitant medications, screening criteria
    Objectives: Understand EDC tools, SDTM and Domains
    Deliverables: Study design, Datasets
    Project Duration: 3 month

18. Draft a simple DMP for Phase 1 study with 50 participants and with all necessary basic requirements emphasising on their importance with justification. Create user roles in any EDC tool. Create datasets and draft an appropriate study design.
    Objectives: DMP overall understanding, study design, datasets
    Deliverables: DMP document with presentation. Study design and datasets creation using SAS programming
    Project Duration: 3 months

19. Draft a complete Study design for PCOS in young children using real world data and select the variables for the datasets: Demographics, Inclusion, exclusion criteria, patient history, Concomitant medications, screening criteria
    Objectives: Understand EDC tools, SDTM and Domains
    Deliverables: Study design, Datasets
    Project Duration: 3 months

20. Create a CRF form(using EDC platform), Dataset with at least 10 variables for a dataset Adverse Event, Concomitant Medications and Patient History, Inclusion and exclusion
    Objectives: Understanding concepts of SAS programming and Adverse event Dataset. Population size of 50 participants, age between 25-55 (Female), Along with medication details. Follow SDTM
    Deliverables: Give a brief Study design and variables justifying the variables, also add concomitant medications and Patient History
    Project Duration: 3 month

COURSE INSTRUCTORS

Bhanu Melvin 
Scientist & Trainer - CDM, PV & RA

Bhanu Melvin, with a strong academic foundation in pharmacy and over a decade of diverse experience across academia, healthcare, regulatory affairs, and corporate training, brings a holistic and agile approach to professional development and organizational excellence. He has successfully trained more than 1,500 individuals, including academic aspirants and industry professionals, in Clinical Research, Pharmacovigilance, Clinical Data Management, Regulatory Affairs, and Clinical SAS Programming. Holding globally recognized certifications in Pharmacovigilance, Lean Six Sigma Black Belt, Clinical Research, Clinical SAS Programming, and ISO 9001:2015 Lead Auditing, he effectively bridges the gap between scientific knowledge, regulatory frameworks, and operational efficiency. Passionate about driving impact, he specializes in designing skill-oriented curricula, strengthening compliance standards, and streamlining clinical workflows to deliver transformative training and strategic solutions tailored to evolving industry needs.

Sushma H
Scientist & Trainer - CDM, PV & RA

Sushma H, an MSc Gold Medalist in Organic Chemistry, has built a strong foundation in scientific research and analytical skills through her academic and professional journey. As a Research Associate at Advarra, she gained hands-on expertise with REDCap for data capture and management, MedDRA coding for standardized adverse event reporting, and CDISC terminologies for regulatory-compliant clinical data submissions, while also developing an in-depth understanding of clinical trial management processes, study workflows, data collection, and quality checks. She further enhanced her career as a Data Scientist at PointCross, working with SDTM standards to assess and analyze various clinical trial phases, generate actionable insights from complex datasets, and support data-driven decision-making throughout the trial lifecycle. Now joining Biotecnika as a Scientific Writer and Trainer, Sushma is set to leverage her research and analytical expertise to create high-quality scientific content and mentor aspiring professionals in the life sciences.

DOWNLOAD BROCHURE

• Aspiring Clinical Data Managers seeking foundational to advanced knowledge in CDM
• Clinical Research Professionals looking to specialize in data management
• Students and professionals in Biotechnology, Life Sciences, and Health Informatics aiming to enter the clinical data field.

What You'll Learn In This Training Program?

1. Comprehensive Knowledge of Clinical Data Management

From Day 1, you’ll explore the definition, scope, and importance of CDM, the clinical trial process, types of trials, and the roles and responsibilities of a CDM professional. You’ll also learn about types of clinical data, their sources, and formats, along with metadata management and an introduction to Clinical Data Management Systems (CDMS).

2. Regulatory Frameworks and Industry Standards

You’ll gain an in-depth understanding of ICH GCP, 21 CFR Part 11, GDPR, ISO standards, CDASH, and SDTM. You’ll also learn the ALCOA+ framework for data integrity, data quality metrics, validation, and verification.

3. Advanced Data Management & EDC Systems

Hands-on training in leading EDC platforms such as REDCap, Medidata Rave, Open Clinica, and Castor. You’ll learn CRF design and customization, data entry, query management, SAE reconciliation, lock/unlock procedures, and data discrepancy handling.

4. SAS Programming Skills for CDM

Practical sessions on SAS programming, including SAS Studio (SAS OnDemand for Academics), data extraction, generating reports, PROC PRINT, PROC STAT, PROC GRAPH, and SDTM-compliant datasets.

5. Practical Implementation & Study Management

Training includes managing mid-study changes, working with CROs, sponsors, and vendors, using Veeva Vault, eConsent, recruitment types, user role management, and dashboard monitoring.

6. Industry Readiness & Career Skills

You’ll explore freelancing opportunities in CDM, roles in regulatory affairs, pharmacovigilance, clinical operations, and clinical research coordination, along with LinkedIn profile optimization.

7. Project Work & Mock Interviews

Work on multiple real-world projects using Open Clinica, Castor EDC, and SAS—covering CRF creation, conditional fields, role-based access control, DMP creation, DBL planning, data normalization, and disease-specific study designs (e.g., diabetes, oncology, dental caries, PCOS). Conclude with mock interview sessions to prepare you for placement.

Benefits of Learning Clinical Data Management (CDM)

1. Growing Demand for CDM Professionals
   Clinical research is expanding rapidly, and CDM experts are in high demand across biotech, pharmaceutical, and healthcare industries.

2. Diverse Career Opportunities
   Mastering CDM opens doors to a variety of roles in clinical trials, data analysis, regulatory compliance, and project management.

3. Industry-Relevant Skill Set
   Gain expertise in critical CDM processes such as eCRF design, regulatory compliance, data standards, query management, and data validation, all of which are essential in today’s clinical research landscape.

4. Competitive Advantage
   With hands-on experience and real-world project training, this course sets you apart from other candidates, giving you a solid edge in job applications.

5. Foundational Knowledge in Compliance Standards
   CDM knowledge equips you with an understanding of compliance with global standards (CDISC, SDTM, ICH-GCP), making you a valuable asset in regulated clinical environments.

6. Long-Term Career Growth
   CDM roles often lead to high-impact positions with opportunities for advancement in clinical research, data analysis, project management, and compliance.

7. Versatile Skill Application
   The skills learned in CDM are transferable across various roles within clinical trials, from data management to biostatistics, expanding your career options.

Benefits of Enrolling

• Hands-On Learning: Gain practical experience that you can directly apply in the workplace. Each module includes activities, quizzes, and projects that cement the knowledge you acquire.
  
  
• Professional Certification: Complete the course to earn a certificate recognized across the clinical research industry. This credential will enhance your resume and validate your expertise to potential employers.
  
  
• Flexible Online Format: With an online schedule, you can learn from anywhere, fitting your studies around existing work or academic commitments.
  
  
• Live Project Experience: By working on real-world projects, you’ll build a portfolio of applied skills, making you a more attractive candidate for clinical data roles.
  
  
• Networking Opportunities: Connect with instructors and other students, creating a network of peers and professionals in the clinical research field.
  
  
• Career Support: Get guidance on how to apply your skills in the workforce, with insights on job roles, application tips, and career growth.