This training program 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. Through case study analysis, the course will examine best practices to provide thoughts and ideas to develop or improve the CDISC mapping system.
This webinar will illustrate 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. Attendees will get a copy of the new CDSIC e-guide and all SAS macros reviewed in class.
Why Should You Attend:
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 webinar will illustrate 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. Attendees will get a copy of the new CDSIC e-guide and all SAS macros reviewed in class.
Learning Objectives:
- 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
Areas Covered in the Webinar:
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
- SUPPDM, SUPPAE, RELREC
- Questionnaire Data
- SDTM Oncology Domains (TU, TR, RS)
- Findings About (FA) - Collection of Different CRFs
- ADaM - DTYPE, Other ex. ADVSLT
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
Course Provider
Sunil Gupta,
