CDISC -ADaM

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What is ADAM?

ADaM defines dataset and metadata standards that support:

  • efficient generation, replication, and review of clinical trial statistical analyses, and
  • traceability among analysis results, analysis data, and data represented in the Study Data Tabulation Model (SDTM).​

ADaM is one of the required standards for data submission to FDA (U.S.) and PMDA (Japan).

Highlights of Course :

  1. Introduction of ADaM
  2. ADSL
  3. OCCDS
  4. BDS
  5. Business logics
  6. Industry Examples with Interview questions
  7. Additional Concepts for above 3 + yrs exp.

Software Installation : Currently software installation is a paid one. You need to do it from system administrator. The total software which consists of around 17 Gb. It will take 2 Hours to do the installation. For SDTM there is no software you need use SAS for SDTM Programming.

System requirements :

Processor : i3 and above

RAM : 4GB and above [preferable 8 GB Best ]

Harddisk : SSD Harddisk with 250 GB OR Above  / other harddisk also its ok

 

Target Audience : To do these SDTM Course you need have the knowledge on

  1. Base sas
  2. Advanced SAS
  3. Clinical Reseach just basic knowlegde
  4. SDTM

Materials : Books and Daily notes will be provided by us along with that recording also will be provided for reference . Step by step notes will be provided and excersises also.

 

Sample Videos : We request you that first don’t join the course directly as we provide the sample videos in the cirriculam first watch that try to understand. If you understand and feel comfortable with trainer explanation then gohead for classes. Join the course.

Working hours  : 9:00 am ist  to 8 pm ist .

ADaM : Analysis data model

Fundamentals of the ADaM Standard

Standard ADaM Variables

1
ADaM Variable Conventions
2
General Variable Conventions
3
Timing Variable Conventions
4
Date and Time Imputation Flag Variables
5
Flag Variable Conventions
6
Variable Naming Fragments

The ADaM Subject-Level Analysis Dataset (ADSL)

1
ADSL Identifier Variables
2
Subject Demographics Variables
3
ADSL Population Indicator Variables
4
ADSL Treatment Variables
5
ADSL Dose Variables
6
Treatment Timing Variables
7
Subject-Level Period, Subperiod, and Phase Timing Variables
8
ADSL Subject-Level Trial Experience Variables
9
More concepts on Extra variables

The ADaM (OCCDS)

1
Working with ADAE Conversions with additional variables
2
Working with ADDS Conversions with additional variables
3
Working with ADCM Conversions with additional variables
4
Working with ADEX Conversions with additional variables

The ADaM Basic Data Structure (BDS)

1
1.Identifier Variables for BDS Datasets
2
2. Record-Level Treatment and Dose Variables for BDS Datasets
3
Record-Level Dose Variables for BDS Datasets
4
Timing Variables for BDS Datasets
5
Period, Subperiod, and Phase Start and End Timing Variables
6
Suffixes for User-Defined Timing Variables in BDS Datasets
7
Analysis Parameter Variables for BDS Datasets
8
PARAM, AVAL, and AVALC
9
Analysis Parameter Criteria Variables for BDS Datasets
10
Analysis Descriptor Variables for BDS Datasets
11
Analysis Visit Windowing Variables for BDS Datasets
12
Time-to-Event Variables for BDS Datasets
13
Toxicity and Range Variables for BDS Datasets
14
Flag Variables for BDS Datasets
15
BDS Population Indicators
16
Datapoint Traceability Variables
17
SDTM and ADaM Population and Baseline Flags diference
18
Creation of Derived Columns versus Creation of Derived Rows
19
Rules for the Creation of Rows and Columns

Working with BDS Conversion specs

1
Working with ADVS Conversion with additional Variables
2
Working with ADLB Conversion with additional variables
3
Working with ADTTE Conversion with additional Variables

Business Logics

1
A parameter-invariant function of AVAL and BASE on the same row that does not involve a transform of BASE should be added as a new column.
2
Creation of a New Parameter to Handle a Transformation
3
Creation of a New Parameter to Handle a Second System of Units
4
Creation of a New Row to Handle a Derived Analysis Timepoint
5
Creation of New Rows to Handle a Derived Analysis Timepoint When There is Value-Level Population Flagging
6
Creation of New Rows to Handle Imputation of Missing Values by Last Observation Carried Forward and Worst Observation Carried Forward
7
Creation of New Rows to Handle Imputation of Missing Values by Baseline Observation Carried Forward and Last Observation Carried Forward
8
Creation of Endpoint Rows to Facilitate Analysis of a Crossover Design

ADaM Methodology and Examples When the Criterion Has Multiple Responses

1
ADaM Dataset with a Criterion that Has Multiple Responses

Extra Topics

1
Paired lab variables
2
Lab visit window techniques
3
Raw/Standard Names/Units
4
ADaM – DTYPE
5
ADAM Metadata Excel file
6
ISO8601 Dates, Partial Dates, Durations and Periods
7
Study Validation Checklists
8
Baseline Values
9
Change, Percent Change from Baseline
10
Imputation Methods
Faq Content 1
Faq Content 2

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Enrolled: 156 students
Duration: 6 Weeks
Lectures: 60
Video: Available
Level: Advanced

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Working hours

Monday 9:00 am to 8 pm ist
Tuesday 9:00 am to 8 pm ist
Wednesday 9:00 am to 8 pm ist
Thursday 9:00 am to 8 pm ist
Friday 9:00 am to 8 pm ist
Saturday 9:00 am to 8 pm ist
Sunday Closed