CDISC Mapping Webinar Series: Comprehensive Training Package (5 Courses)

This comprehensive training series will discuss CDISC requirements to create SDTMs and ADaMs. It will also offer essential mapping and strategy concepts for creating and validating SDTM and ADaM variables in key CDISC datasets (DM, AE, ADSL, and ADAE). The five-part training program will each focus on different areas of CDISC mapping, including: a review and comparison of SDTM and ADaM dataset structures, a mapping plan from raw datasets to SDTM to ADaM datasets, key differences between SDTM and ADaM models and process flows, key differences between the seven CDISC classes, best practices to create Dataset.XML from SAS, and more.

The flexible program module allows participants to choose any or all trainings. Participants will be trained on utilizing metadata to automatically assign variable attributes in SDTMs and ADaMs, understand the structure and syntax of ODM-XML files, and gain a clear understanding of the nine steps to SDTM mapping and seven steps to ADaM mapping. The sessions will also encourage participants to effectively create and process ISO8601 dates, paired lab variables, as well as impart lab visit window techniques, and effective techniques for using PROC TRANSPOSE to create and merge SUPPXX datasets with SDTMs to create ADAMs.

CDISC Mapping 1: Specifications and FDA Requirements

Areas Covered in the Webinar:

• 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

CDISC Mapping 2: ODM, MindMaps and References

Areas Covered in the Webinar:

• 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

CDISC Mapping 3: Compare and Contrast SDTM and ADaM Steps

Areas Covered in the Webinar:

• 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

CDISC Mapping 4: SDTMs and ADAMs Examples (80%/20% Mapping Rule)

Areas Covered in the Webinar:

1. 80% General Variables
1. 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
2. ADaM
• Analysis Variables
• Imputation Methods
• Baseline Identification
• Visit Windows and Unscheduled Visits
• ADSL, ADAE
2. 20% Special Variables
• SDTM
• SUPPDM, SUPPAE, RELREC
• Questionnaire Data
• SDTM Oncology Domains (TU, TR, RS)
• Findings About (FA) – Collection of Different CRFs
• ADaM - DTYPE, Other ex. ADVSLT

CDISC Mapping 5: ADAM Models - ADSL, BDS and ADAE

Areas Covered in the Webinar:

• 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

Who Will Benefit:

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.

• 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

Instructor Profile:

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, SASSavvy.com, for smarter SAS searches. Currently, SAS Savvy’s membership consists mostly of SAS programmers, university students and pharmaceutical corporate accounts.

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