G-8N662TLNBB
 

Clinical SAS Online Training

INTRODUCTION 

The Process from discovering a new drug to registering it for marketing is very complex and lengthy. There are several people involved in the Process of drug discovery and development includes Scientists, Clinicians, Statisticians as well as Data managers and SAS Programmers. It is estimated that, on average, a drug takes 10-12 years from initial research to reach the market. Drug discovery and development are mainly carried out by pharmaceutical companies and research agencies. The pharmaceutical market is very competitive. It is imperative that pharmaceutical companies discover and develop drugs efficiently and within the shortest time span to remain competitive.

CDISC SDTM AND ADaM Online Training

INTRODUCTION 

CDISC /SDTM fundamental model for organizing data collected in clinical trials.CDISC is a global, open, multidisciplinary, non-profit organization non profit that has established standards to support the acquisition, exchange, submission and archive of clinical research data and metadata.It is for “Good data management practices” are essential to the success of a trial because they help to ensure that the data collected is complete and accurate

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What is CDISC ?

CDISC Concept of Observations, which consist of discrete pieces of information collected during a study described by a series of named variables. General Classes of Observations: Events, Findings, Interventions Variable Roles: determines the type of information conveyed by the variable about each distinct observation: Topic variables, Identifier variables, Timing variables, Rule variables, and Qualifiers (Grouping, Result, Synonym, Record, Variable) General principles and standards

CDISC SDTM’s fundamental model for organizing clinical data
The patient/subject focused information model of the clinical ‘reality’ (general classes of observations on subjects: interventions, findings, events). This model has been developed by CDISC/SDS team and exist today only as a text description

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Study Data Tabulation Model (SDTM): – The content standard for regulatory submission of case report form data tabulations from clinical research studies.

Analysis Data Model (ADaM): – The content standard for regulatory submission of analysis datasets and associated files.• Case Report Tabulation Data Definition Specification (CRTDDS) (define.xml)
The XML-based content and format standard referenced by the FDA as the specification for the data Definition for CDISC SDTM datasets. This standard, also known as define.xml,is an extension of the ODM.

       IN THIS COURSE YOU CAN LEARN

INTRODUCTION to CDISC and Maping
FUNDAMENTALS OF THE SDTM
SUBMITTING DATA IN STANDARD FORMAT
ASSUMPTIONS FOR DOMAIN MODELS
GENERAL ASSUMPTIONS FOR ALL DOMAINS
General Variable Assumptions
Coding and Controlled Terminology Assumptions
Actual and Relative Time Assumptions
Other Assumptions
MODELS FOR SPECIAL-PURPOSE DOMAINS
DEMOGRAPHICS
COMMENTS
SUBJECT ELEMENTS AND VISITS
Subject Elements — SE
Subject Visits — SV
DOMAIN MODELS BASED ON THE GENERAL OBSERVATION CLASSES
INTERVENTIONS
Concomitant Medications — CM
Exposure — EX
Substance Use — SU
EVENTS
Adverse Events — AE
Disposition — DS
Medical History — MH
Protocol Deviations — DV
Clinical Events — CE
FINDINGS .124
ECG Test Results — EG
Inclusion/Exclusion Criteria Not Met — IE
Laboratory Test Results — LB
Physical Examination — PE
Questionnaire — QS
Subject Characteristics — SC
Vital Signs — VS
Drug Accountability — DA
Microbiology Domains — MB and MS
Microbiology Susceptibility (MS) Domain Model
Pharmacokinetics Domains — PC and PP
FINDINGS ABOUT EVENTS OR INTERVENTIONS
TRIAL DESIGN DATASETS
INTRODUCTION
TRIAL ARMS
Issues in Trial Arms Datasets
TRIAL ELEMENTS
TRIAL VISITS
Trial Visits Dataset — TV
Assumptions for TV Dataset
Trial Visits Examples
Trial Visits Issues
TRIAL INCLUSION/EXCLUSION CRITERIA
TRIAL SUMMARY INFORMATION
HOW TO MODEL THE DESIGN OF A CLINICAL TRIAL
REPRESENTING RELATIONSHIPS AND DATA
RELATING GROUPS OF RECORDS WITHIN A DOMAIN USING THE –GRPID VARIABLE
GRPID Example
RELATING PEER RECORDS
RELREC Dataset
RELREC Dataset