ANALYSIS DATA MODEL (ADaM) - Qtech-Sol offers Clinical Research / Trials, Pharmacovigilance, Drug Safety, Clinical Data Management, Clinical SAS Programming and Healthcare BA Training Programs
Category:
Analytics and Reporting
 
Duration:
3 Weeks / 80 Hours
 

Analysis Data Model

Introduction – Analysis Data Model (ADaM)

The Analysis Data Model (ADaM), developed by CDISC, provides the standard structure for organizing and analyzing clinical trial data. While SDTM focuses on submission-ready datasets, ADaM enables the creation of analysis-ready datasets that support statistical reporting, regulatory review, and generation of Tables, Listings, and Graphs (TLGs).
The ADaM program equips learners with the skills to transform SDTM data into compliant ADaM datasets, apply derivations, and ensure traceability from raw data to statistical results. This training is essential for statistical programmers, biostatisticians, and regulatory submission specialists working in FDA/EMA-regulated environments.

Course Name :  Analysis Data Model (ADaM)
Course Code :  ADAM
Experience Level :  Intermediate to Advanced
Qualification :  Bachelor’s / Master’s in Statistics, Computer Science, Life Sciences, or related fields
Student Category :  Statistical Programmers, Biostatisticians, Clinical Data Managers, Regulatory Submission Specialists

Delivery Type

SIP – Self-Paced Online with Support

Duration & Delivery
  1. Course Duration: 3 weeks (80 hours)
  2. Format: Self-Paced Online with Support ((narrated lessons, readings, quizzes, and role-based tasks).
Key Learning Objectives

   By completing this program, learners will:

  1. Understand the purpose and structure of ADaM datasets in clinical research.
  2. Learn about ADaM standards and implementation guides (ADaMIG).
  3. Explore ADaM dataset classes (ADSL, BDS, OCCDS).
  4. Apply derivations and algorithms for analysis variables.
  5. Ensure traceability between SDTM → ADaM → TLGs.
  6. Work with compliance tools (Pinnacle 21, OpenCDISC).
  7. Understand the role of ADaM datasets in regulatory submissions (FDA, PMDA, EMA).
  8. Gain practical experience with programming examples and case studies.
Who Should Take This Course

This program is ideal for:

  1. Statistical Programmers / SAS Programmers supporting regulatory submissions.
  2. Biostatisticians designing analyses and TLG outputs.
  3. Clinical Data Managers ensuring compliance with CDISC standards.
  4. Regulatory submission professionals working with ADaM datasets.
Benefits & Outcomes

This program is ideal for:

  1. Gain hands-on experience in building ADaM datasets.
  2. Ensure traceability and compliance with CDISC standards.
  3. Improve readiness for regulatory inspections and audits.
  4. Build a foundation for advanced programming in TLGs and statistical reporting.
  5. Enhance employability for roles in pharma, CROs, and regulatory submissions.
Career Pathways: After completing this course.
  1. Statistical Programmer (ADaM/SDTM Specialist)
  2. Clinical Data Standards Specialist
  3. Biostatistical Analyst
  4. Regulatory Submission Programmer
  5. Clinical Programming Lead

Curriculum & Modules

Modules
1. Introduction to ADaM and CDISC Standards

2. ADaM Implementation Guide (ADaMIG) Overview

3. ADaM Dataset Classes (ADSL, BDS, OCCDS)

4. Understanding Analysis Variables & Derivations

5. ADaM Metadata, Define.xml, and Traceability Rules

6. Linking SDTM → ADaM → TLGs

7. Statistical Algorithms in ADaM (e.g., time-to-event, change-from-baseline)

8. Common ADaM Issues & Compliance Checks

9. Regulatory Expectations for ADaM Submissions (FDA, PMDA, EMA)

10. Case Studies – Building ADaM Datasets from SDTM

Getting in Touch:

For more information, please call us at +91 8925971788 / +91 8977943100 (WhatsApp)or email qpdc@qtechelearncenter.com. Our course specialists will reach out to you promptly to assist you in taking the next steps toward your career goals.