Course Description:

CDISC requirements to create SDTMs and ADaMs are not easy to understand or apply. There are many rules and standards that must be mastered and maintained across global studies. Pharmaceutical companies and CROs supporting global studies have a need to apply proven methods that reduce confusion and improve documentation. With new members joining the study team, there should be a system to help standardize and automate the FDA submission process.

This two day workshop teaches essential mapping and strategy concepts for creating and validating SDTM and ADaM variables in key CDISC datasets (DM, AE, ADSL, and ADAE). Examples of both SDTM and ADaM dataset structures will be reviewed and compared. In addition, a mapping plan from raw datasets to SDTM to ADaM datasets will also be outlined. To help assure higher quality clinical data, a qc checklist and some key edit check macros will be introduced. Students will get a copy of the new CDSIC e-guide and all SAS macros reviewed in class. All students will get a one month free trial premium membership to for making smarter SAS searches. Through case study analysis we will examine best practices to provide thoughts and ideas to develop or improve the CDISC mapping system.

Learning Objective:

Upon completing this course participants should:

  • Better understand ODM and SDM models
  • Better understand how SDTM and ADaM metadata play an important role to automate the process
  • Know how to maintain control terminology and value level metadata
  • Better understand differences and purpose of DEFINE.XML and DEFINE.PDF

Seminar Fee Includes:

AM-PM Tea/Coffee
Seminar Material
USB with seminar presentation
Hard copy of presentation
Attendance Certificate
$100 Gift Cert for next seminar

  • Understand key differences between SDTM and ADaM Models and Process Flows
  • Understand key differences between the Seven CDISC Classes
  • How to create Dataset.XML from SAS
  • Better understand structure and syntax of ODM-XML files using examples
  • Understand the differences between the four different variable roles and three different variable types
  • Better understand the nine steps to SDTM mapping and seven steps to ADaM mapping
  • Better understand raw data, dataset joins and traceability concepts
  • Utilize metadata to automatically assign variable attributes in SDTMs and ADaMs
  • Create and process ISO8601 dates, hierarchy of adverse events variables, paired lab variables, as well as lab visit window techniques
  • Apply effective techniques for using PROC TRANSPOSE to create and merge SUPPXX datasets with SDTMs to create ADaMs
  • Be better prepared for the SAS Clinical Trials Certification exam
  • Utilize metadata to automatically assign variable attributes in ADaMs
  • Create and process ISO8601 dates, hierarchy of adverse events variables
  • Better understand the purpose of running OpenCDISC
  • Submit better FDA submissions by better understanding the technical and process review

Who Will Benefit:

This course is intended for anyone directly or indirectly responsible for the creation, content or validation of CDISC data sets, tables, and data lists used to support research, drug or medical device efficacy and safety in a regulatory submission. Professionals in the pharmaceutical, biotechnology and medical device industries who want to be Good Clinical Practices (GCP) compliant in relation to regulatory submission environment will benefit from this unique course. Effective and practical solutions to address real-world issues will be provided.

This course is recommended for:

  • SAS Statistical Programmers
  • Quality Assurance Specialists
  • SAS Statistical Managers
  • Medical Writers
  • Statisticians
  • Regulatory Affairs Associates
  • Clinical Data Managers
  • Directors, Statistical Programming
  • CRO Professionals
  • Health Care Professionals
  • Research University Specialists

Course Outline:

Day 1 (8:30 AM – 4:30 PM) Day 2 (8:30 AM – 4:30 PM)
  • Understanding CDISC terms
  • ODM and SDM Map – The Big Picture
  • CDASH, Study Data Standardization Plan and Submission Data Standards
  • SDTMs and ADaMs Specifications
  • Metadata files and Control Terminology
  • CDISC Reference and Guides
  • DEFINE.XML and DEFINE.PDF – Differences and examples
  • MindMaps - SDTM and ADaM Domains, SDTM Variable Types and Roles
  • CDISC Quick References
  • Understanding Seven CDISC Classes
  • Study Reference Files
  • SDTM and ADaM Dataset Models and Process Flows
  • Creating and QCing Define.xml & Dataset-XML
  • Creating Dataset.XML from SAS
  • ODM-XML file structure and content
    • Global Element Order
    • Understanding Tagsets
    • Components – Metadata, Clinical Data, Administrative, Reference and Audit
  • Compare SDTM and ADaM – Key Differences
  • When are Key SDTM/ADaM Variables Created
  • Mapping Raw Data to SDTMs by SDTMs
  • Nine Step SDTM Mapping Plan
    • Confirm Date Variables
    • SDTM Mapping of Study Day, ex AESTDY
    • Three types of Raw Data collected
    • Three types of Dataset Joins
    • Match DM Variables: Three Types of Raw Variable Mapping to SDTMs
  • Seven Step ADaM Mapping Plan
    • ADaM Model Concepts
    • ADaM Six Levels of Flag Variables
    • ADaM BDS Variable Types
    • Three ADaM Models
    • Traceability
    • ADaM Mapping Plan – Analysis visit windows
    • ADLB – DTYPE=‘XXX’ New Records
  • 80% General Variables
  • SDTM
    • Mapping to SDTM Variables: Four Types
    • Apply one of seven mapping methods
    • Eight Variable Types Based on Values
    • Control Terminology – Format Metadata from CODELISTS tab
    • SDTM Metadata Excel file
    • AE MedDRA Hierarchy Structure
    • Purpose of Trial Designs: Trial Elements, Trial Arms and Trial Visits
    • DM, AE, EX, SE, SV
  • ADaM
    • Analysis Variables
    • Imputation Methods
    • Baseline Identification
    • Visit Windows and Unscheduled Visits
    • ADSL, ADAE
  • 20% Special Variables
  • SDTM
    • Questionnaire Data – Online Reference
    • SDTM Oncology Domains (TU, TR, RS)
    • Findings About (FA) – Collection of different CRFs
  • ADaM - DTYPE, Other ex. ADVSLT
  • ADAM Metadata Excel file
  • ISO8601 Dates, Partial Dates, Durations and Periods
  • Study Validation Checklists
  • SDTM and ADaM QC Forms
  • OpenCDISC and SAS Clinical Standard Toolkit
  • Templates – SDTM and ADaM Specifications, Defaults, Master SDTM to ADaM Map
  • ISS/ISE – Master Control Terminology
  • Understanding the FDA Review process and preventing delays - FDA’s High Expectations
  • Understanding how to avoid FDA Review issues – Challenges
  • Sponsor’s Best Practices for better FDA Submissions - Lessons Learned
    • Paired lab variables
    • Lab visit window techniques
    • Raw/Standard Names/Units
    • Baseline Values
    • Change, Percent Change from Baseline
    • Imputation Methods

Meet Your Instructor

Sunil Gupta,
CDISC Consultant and Trainer | SAS Programmer and Mentor | Best-Selling SAS Author

Sunil Gupta is an international speaker, best-selling SAS author, and a global corporate trainer. He is the principal SAS/CDISC consultant at Gupta Programming since 1994. Most recently, he taught both of his CDISC online classes with the University of California at San Diego and SAS Institute India. Mr. Gupta will start to teach the new Sharpening Your SAS Skills online class for UCLA Extension in 2016. In 2011, he launched his unique SAS resource blog,, for smarter SAS searches. Currently, SAS Savvy’s membership consists mostly of SAS programmers, university students and pharmaceutical corporate accounts.

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