Master SDTM for Clinical Data Management with Encode-IT’s Comprehensive Course

The Study Data Tabulation Model (SDTM) is a critical standard developed by the Clinical Data
Interchange Standards Consortium (CDISC) for organizing and formatting clinical trial data. It plays a
crucial role in ensuring that data from clinical studies is consistent, standardized, and compliant with
global regulatory requirements. The SDTM course at Encode-IT is designed to provide an in-depth
understanding of SDTM standards, equipping professionals with the skills needed to manage and
analyze clinical data efficiently.

This course covers the full scope of SDTM, from the basics of the model to the implementation of
advanced features for regulatory submissions. You’ll learn how to organize clinical data in
accordance with SDTM standards, map raw data to SDTM domains, and create datasets that are
ready for submission to regulatory agencies like the FDA and EMA. By the end of the course, you will
have hands-on experience in preparing SDTM datasets, ensuring compliance, and delivering accurate
results in clinical trials.

Salary Prospects in India:
In India, professionals skilled in SDTM and clinical data management are highly sought after,
particularly in the pharmaceutical, biotechnological, and clinical research sectors. Depending on
experience, professionals working with SDTM can expect salaries ranging from ₹7 to ₹18 lakhs
annually. Senior roles, such as Clinical Data Manager or SDTM Programmer, can command salaries
upwards of ₹20 lakhs per year, especially for those involved in regulatory submissions and large-
scale clinical trials. With increasing demand for compliance and regulatory expertise, SDTM
specialists enjoy strong career prospects and competitive salaries.

Placement Assistance & Certification:
Encode-IT is dedicated to your career growth and success. Along with this SDTM course, we provide
Placement Assistance to help you connect with top companies in the clinical research and
pharmaceutical industries. Our placement services include interview coaching, resume building, and
access to job openings at leading firms in the healthcare and clinical trial domains.

Upon completion of the course, you will receive a Certificate of Completion from Encode-IT, which
will serve as a strong credential for securing roles in clinical data management and clinical trial
analysis. This certification demonstrates your expertise in SDTM and positions you for success in
your career.

Course Curriculum:

Module 1: Introduction to Clinical Data Management and SDTM
 Overview of Clinical Trials and the Role of Data Management
 Introduction to SDTM and Its Importance in Regulatory Submissions
 Key Components of SDTM: Domains, Variables, and Controlled Terminology
 Regulatory Requirements for Clinical Data: FDA, EMA, and ICH Guidelines
 Overview of CDISC Standards and the SDTM Model

Module 2: Understanding SDTM Domains and Datasets

 Overview of SDTM Domains: Demographics, Adverse Events, Laboratory, and More
 Mapping Raw Data to SDTM Domains
 Creating SDTM Datasets for Regulatory Submission
 Introduction to Standard SDTM Variables and Controlled Terminology
 Organizing Data into SDTM Domains: Key Steps and Best Practices

Module 3: SDTM Structure and Dataset Components
 Detailed Breakdown of SDTM Dataset Components: Records, Variables, and Attributes
 Understanding the Structure of SDTM Datasets and Their Relationships
 Working with Core Variables and Domain-Specific Variables
 Implementing Consistent Coding in SDTM Datasets
 Handling Missing Data and Special Variables in SDTM

Module 4: Implementing SDTM for Clinical Trial Data
 Organizing Raw Clinical Data into SDTM Format
 Working with Multiple Domains in a Single SDTM Dataset
 Mapping Data to the Appropriate SDTM Domains and Variables
 Transformation of Raw Data into SDTM Compliant Datasets
 Handling Complex Data Types: Time, Date, and Categorical Data

Module 5: SDTM Submission Guidelines and Compliance
 Overview of Regulatory Submission Requirements for SDTM Datasets
 Preparing SDTM Datasets for FDA and EMA Submissions
 Ensuring Compliance with 21 CFR Part 11 and GxP Regulations
 Validation and Quality Control of SDTM Datasets for Submissions
 Tools and Techniques for SDTM Validation and Submission

Module 6: Using SAS for SDTM Programming
 Introduction to SAS for SDTM Data Preparation
 Creating SDTM Datasets Using SAS Procedures
 Handling Raw Data Using SAS Import and Export Procedures
 Data Transformation and Mapping with SAS: A Practical Guide
 Ensuring Data Quality and Validation with SAS Tools

Module 7: Advanced SDTM Concepts and Best Practices
 Advanced SDTM Domain Mappings: Case Studies and Examples

 Handling Special Data Structures: Events, Findings, and Multivariable Data
 Best Practices for SDTM Documentation and Traceability
 Leveraging CDISC Controlled Terminology and Data Standards
 Managing SDTM in Multi-Site and Global Clinical Trials

Module 8: SDTM and Data Integration
 Integrating SDTM Data with Other Clinical Trial Data Models
 Working with ADaM (Analysis Data Model) and SDTM in Regulatory Submissions
 Mapping and Integrating SDTM Datasets with ADaM for Statistical Analysis
 Data Harmonization for Multi-Country and Multi-Center Trials
 Addressing Challenges in Integrating SDTM Data Across Platforms

Module 9: Real-World SDTM Case Studies
 Analyzing Real-World Clinical Trial Datasets: Case Studies
 Identifying Common Issues in SDTM Data and How to Solve Them
 Implementing SDTM in Large-Scale Clinical Trials: Challenges and Solutions
 Preparing SDTM for Post-Marketing Studies and Drug Safety Surveillance
 Review of Completed SDTM Datasets for Quality Assurance

Module 10: Final Project and Certification Exam
 Final Project: Preparing a Complete SDTM Dataset for a Hypothetical Clinical Trial
 Data Mapping, Validation, and Final Submission Preparation
 Project Evaluation and Feedback
 Final Exam: Comprehensive Test on SDTM Standards and Techniques
 Certification of Completion from Encode-IT and Job Placement Assistance

Key Features of the Course:                                                                                                                                                                                       Tools & Platforms: SAS, CDISC, SDTM, Clinical Trial Management Systems (CTMS)
 Real-World Projects: Hands-on experience in preparing SDTM datasets and mapping raw
data
 Certification & Placement Support: Encode-IT certification and job placement assistance in
clinical data management
 Expert Instructors: Learn from industry professionals with extensive experience in clinical
data management and SDTM programming
 Career Advancement: Gain the skills necessary to work with SDTM in clinical trials and
regulatory submissions

By completing the SDTM course at Encode-IT, you will be equipped with the knowledge and
practical experience to manage clinical data in compliance with regulatory standards. Whether
you’re aiming to become a clinical data manager, clinical programmer, or data analyst, this course
will prepare you for a successful career in the field of clinical trials and data management.