Clinical SAS Project ADAM Training for Beginners👍CDISC SDTM ADAM TLFS Training Complete Process Flow

Clinical SAS Project ADAM Training for Beginners CDISC SDTM ADAM TLFS Training Complete Process Flow ADaM (Analysis Data Model): ADaM describes how to build analysis datasets and associated metadata. This in turn allows a developer to generate TLF (tables, listings and figures) more easily and ensures traceability. That means, reviewers can review and approve a submission quickly. The ADaM is a standard structure, which is built from SDTM. The fundamental principle is data traceability, which means that the variable in ADaM track back from corresponding SDTM domains and from there back to the eCRF. ADaM principles: 1. Facilitates clear communication (No scope for ambiguity) 2. Provides traceability between the analysis data and its source data (SDTM) 3. Be accompanied by metadata 4. Be analysis-ready ADaM Vs SDTM: ADaM ties closely with SDTM though they have different functions. While SDTM is used to create and map collected data from raw sources, ADaM is all about creating data that is ready for the analysis. SDTM is always the source of ADaM data. Traceability: Defines relationship between the analysis results the analysis datasets and SDTM domains Example: Reviewer can trace how the primary and secondary efficacy values are derived from SDTM data for each subject. Roles: Any variables in an ADaM dataset whose name is same as SDTM variable must be a direct copy of SDTM variable - name, its label , meaning and values must not be modified. Standard ADaM variables (core): Required Variables: must be included in the dataset Permissible variables: variables can be included depending upon the needs of sponsor Conditional variables: variables must be included in the datasets in certain circumstances. ================== ADaM standard structures: 1. Subject level analysis datasets (ADSL) 2. Basic Data Structures (BDS) and 3. Occurrence Data Structure (OCCDS) Subject level information --- ADSL Findings information --- BDS (Basic Dataset Structure) --- ADLB (ADSL + LB) , ADVS (ADSL + VS) Events/Interventions --- Occurrence Data Structures --- ADAE (ADSL + AE) , ADCM (ADSL + CM) 1. Subject level analysis datasets (ADSL) ADSL is an important domain that describes a subject's experience in the clinical trails, which is applied to all types of analysis. DM is the primary source. ADSL 2. BDS model allows any type of by visit data (LB, EG, VS, by-visit efficacy,...) to be created. SDTM finding domains are the primary source of data. ADaM datasets must have the variable parameter (PARAM) and analysis variable (AVAL) ADEG ADLB ADVS ADDA 3. OCCDS model is designed for occurrences that do not happen at a specific visit such as AE and CM. SDTM Interventions and Events are the primary sources of data. ADAE ADCM ADMH =============================================== Flow: Raw data -- SDTM output -- ADAM output --- TLF ADAM Documents/resources (pre-req): Protocol SDTM output datasets ADAM Implementation guide (v1.1) ADAM specification doc Tool (SAS) SDTM Vs ADAM: ================================================