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COURSES WE OFFER

CLINICAL RESEARCH/CLINICAL TRIAL MANAGEMENT

  • ➔ Clinical Research History
  • ➔ ICH GCP Guidelines
  • ➔ Pre Clinical Research
  • ➔ Pharmacovigilance
  • ➔ Protocol

Phases:

  • ✔ Phase I
  • ✔ Phase II
  • ✔ Phase III
  • ✔ Phase IV

Trail Design:

  • ✔ ARMS
  • ✔ Randomization
  • ✔ Blinding
  • ✔ Parellel
  • ✔ Crossover
  • ✔ Interpretation of Time & Event Schedule
  • ➔ E2A Guidelines
  • ➔ E2B Guidelines
  • ➔ Investigator Brochure
  • ➔ Inform Consent
  • ➔ Source Documents
  • ➔ LOGS
  • ➔ Trial Master Files
  • ➔ Ethics Commitee
  • ➔ Site Feasiblity
  • ➔ Site Initiation
  • ➔ Site Monitoring
  • ➔ Site Close Out
  • ➔ Roles of Investigator, CRC, CRA, Sponsor
  • ➔ Walk Through the Steps from Subject Recruitment to Subject Completion of Study with Real Time Scenario's.

CLINCAL DATABASE PROGRAMMING (STUDY BUILD)

  • ➔ EDC Architecture
  • ➔ CRF Development Specifications
  • ➔ eCRF Designing (on EDC Tool)
  • ➔ Data Validation Specification
  • ➔ Offline Checks
  • ➔ Data Validation Programming
  • ➔ External Lab Specifications
  • ➔ External Lab Specifications Programming (SAS)
  • ➔ SAE Reconciliation Specifications
  • ➔ SAE Reconciliation Specifications Programming (SAS)
  • ➔ Test Data Preparation
  • ➔ User Acceptance Testing (UAT)
  • ➔ Pharmacovigilance

DATA VALIDATION DEPARTMENT/DATA PROCESSING DEPARTMENT:

  • ✔ CRF Tracking
  • ✔ Data Entry
  • ✔ Batch Validation Procedures
  • ✔ Query Management (on EDC Tool)
  • ✔ Coding (MEDRA and WHO)
  • ✔ Lab Reconciliation
  • ✔ SAE Reconcialition
  • ✔ Export Data Extraction
  • ✔ Vendor Management
  • ✔ EDC Tool Navigation (Understanding Different Feature in EDC Tool)
  • ✔ Database Lock

CDISC-SDTM

  • ➔ Introduction
  • ➔ Fundamentals of SDTM
  • ➔ Submitting Data in Standard Format
  • ➔ Assumption for Domain Models

STUDY DATA TABULATION MODEL (SDTM):

  • ✔ INTRODUCTION TO SDTM
  • ✔ CRF ANNOTATION
  • ✔ MAPPING SPECIFICATIONS
  • ✔ SDTM PROGRAMMING

SUBMITTING DATA IN STANDARD FORMAT:

  • ✔ Standard Metadata for Dataset Contents and Attributes
  • ✔ Using the CDISC Domain Models in Regulatory Submissions - Dataset METADATA
    • Primary Keys
    • CDISC Submission Value-Level Metadata
    • conformance

MODELS FOR SPECIAL-PURPOSE DOMAINS:

  • ✔ Demographics
  • ✔ Comments
  • ✔ Subject Elements
  • ✔ Subject Visits

DOMAIN MODELS BASED ON THE GENERAL OBSERVATION CLASSES:

  • ✔ Interventions
  • ✔ Events
  • ✔ Findings
  • ✔ Findings about

TRIAL DESIGN DATA SETS:

  • ✔ Introduction
  • ✔ Trial Arms
  • ✔ Trial Elements
  • ✔ Trial Visits
  • ✔ Trial Inclusion/Exclusion Criteria
  • ✔ Trial Summary Information
  • ✔ How to Model the Design of a Clinical Trial

REPRESENTING RELATIONSHIPS AND DATA:

  • ✔ Relating Group of Records Within a Domain Using the Grpid Variable
  • ✔ Relating Peer Records
  • ✔ Relating Datasets
  • ✔ Relating Non-Standard Variables Values to a Parent Domain
  • ✔ Relating Comments to A Parent Domain
  • ✔ How to Determine where Data Belong in the SDTM
  • ✔ Trial Design Datasets
  • ✔ Representing Relationships And Data
  • ✔ Models for Special Purpose Domains
  • ✔ Domain Models Based on General Observation Classes

FUNDAMENTALS OF THE SDTM:

  • ✔ Observations and Variables
  • ✔ Datasets and Domains
  • ✔ Special-Purpose Datasets
  • ✔ The General Observation Classes
  • ✔ The SDTM Standard Domain Models
  • ✔ Creating a New Domain

ASSUMPTIONS FOR DOMAIN MODELS:

GENERAL ASSUMPTIONS FOR ALL DOMAINS:

  • ✔ General Domain Assumptions
  • ✔ Review Study Data Tabulation and Implementation Guide
  • ✔ Relationship to Analysis Datasets
  • ✔ Additional Timing Variables
  • ✔ Order of the Variables
  • ✔ CDISC Core Variables
  • ✔ Additional Guidance on Dataset Naming
  • ✔ Splitting Domains
  • ✔ Origin Metadata
  • ✔ Assigning Natural Keys in the Metadata

GENERAL VARIABLE ASSUMPTIONS:

  • ✔ Variable-Naming Conventions
  • ✔ Two-Character Domain Identifier
  • ✔ Use of "Subject" and USUBJID
  • ✔ Case Use of Text in Submitted Data
  • ✔ Grouping Variables and Categorization
  • ✔ Submitting Free Text from the CRF
  • ✔ Multiple Values for a Variable

CODING AND CONTROLLED TERMINOLOGY ASSUMPTIONS:

  • ✔ Types of Controlled Terminology
  • ✔ Controlled Terminology Text Case
  • ✔ Controlled Terminology Values
  • ✔ Use of Controlled Terminology and Arbitrary Number Codes
  • ✔ Storing Controlled Terminology for Synonym Qualifier Variables
  • ✔ Storing Topic Variables for General Domain Models
  • ✔ Use of "Yes" and "No" Values

ACTUAL AND RELATIVE TIME ASSUMPTIONS:

  • ✔ Formats for Date/Time Variables
  • ✔ Formats for Date/Time Variables
  • ✔ Intervals of Time and Use of Duration for -DUR Variables
  • ✔ Use of the "Study Day" Variables
  • ✔ Clinical Encounters and Visits
  • ✔ Representing Additional Study Days
  • ✔ Use of Relative Timing Variables
  • ✔ Date and Time Reported in a Domain Based on Findings
  • ✔ Use of Dates as Result Variables
  • ✔ Representing Time Points

OTHER ASSUMPTIONS:

  • ✔ Original and Standardized Results of Findings and Tests Not Done
  • ✔ Linking of Multiple Observations
  • ✔ Text Strings That Exceed the Maximum Length for General-Observation-Class Domain Variables
  • ✔ Evaluators in the Interventions and Events Observation Classes
  • ✔ Clinical Significance for Findings Observation Class Data
  • ✔ Supplemental Reason Variables
  • ✔ Presence or Absence of Pre-Specified Interventions and Events

Base SAS

  • ➔ Basic Five Main Windows: Explorer, Program Editor, Log, Output and Result Windows
  • ➔ User Enhanced Editor Windows
  • ➔ MANAGE YOUR SAS WINDOWS
  • ➔ Manage your SAS Windows
  • ➔ Create SAS Libraries
  • ➔ Explore and Manage SAS Files
  • ➔ Enter and Submit SAS Programs
  • ➔ Create and Use File Shortcuts

BASIC CONCEPTS:

  • ✔ The Steps Involve in Processing SAS Programs
  • ✔ Structure and Component of SAS Dataset
  • ✔ Temporary and Permanent SAS Libraries
  • ✔ Reading the SAS Log
  • ✔ Using SAS System Option

READING RAW DATA:

  • ✔ Reference a SAS Data Library
  • ✔ Reference a Raw Data File
  • ✔ Name a SAS Data Set to be Read
  • ✔ Specify a Raw Data File to be Read
  • ✔ Read Standard Character and Numeric Values in Fields
  • ✔ Submit and Verify a Data Step Program
  • ✔ Distinguish Between Standard and Nonstandard Numeric Data
  • ✔ Read Standard Field Data
  • ✔ Read Non Standard Field Data
  • ✔ Free-Format Data Separated by Nonblank Delimiters, Such as Commas
  • ✔ Free-Format Data that Contains Missing Values
  • ✔ Character Values that Exceed Eight Characters
  • ✔ Character Values that Contain Embedded Blanks
  • ✔ Controlling Input with Options in the in File Statements

CREATING MULTIPLE OBSERVATION FROM A SINGLE RECORD:

  • ✔ Create Multiple Observation from Single Record that Contains Repeating Blocks of Data
  • ✔ Hold the Current Record across Iterations of the Data Step
  • ✔ Hold the Current Record for the next input Statement
  • ✔ Execute SAS Statements based on a Variable's Value
  • ✔ Explicity Write an Observation to a Data Set
  • ✔ Execute SAS Statement while a Condition is True

GENERATING DATA WITH DO LOOPS:

  • ✔ Construct ado Loop to Perform Repetitive Calculation
  • ✔ Control the Execution of do Loop
  • ✔ Generate Multiple Observations in one Iteration of the Data Step
  • ✔ Construct Nested do Loops

READING DATE AND TIME VALUES:

  • ✔ How SAS Software Stores Date and Time Values
  • ✔ To Read Common Date and Time Expression Using SAS Informats

WORKING WITH SAS DATA:

  • ✔ Identify the Two Phases that Occur when a Data Step is Processed
  • ✔ Identify the Processing Phase in which an Error Occur

READING,CONCATENATING AND MERGING SAS DATA SETS:

  • ✔ Create a New Data Set from One or More Existing Data Set
  • ✔ Select Observation based on a Condition
  • ✔ Select Variables TI Include or Exclude
  • ✔ Using if then Statements
  • ✔ Grouping Observation with if - then/Else Statements
  • ✔ Sub Setting your Data
  • ✔ Selected Date Informats, Formats
  • ✔ Using the Retain and Sum Statements
  • ✔ Using Shortcuts for Lists of Variable Names
  • ✔ Using SAS Data Set Options
  • ✔ Tracking and Selecting Observations with the in= Option
  • ✔ Writing Multiple Data Sets Using the Output Statement
  • ✔ Making Several Observations from One Using the Output Statement

TRANSFORMING DATA WITH SAS FUNCTIONS:

  • ✔ Convert Character Data to Numeric Data
  • ✔ Convert Numeric Data to Character Data
  • ✔ Create SAS Date Values
  • ✔ Extract the Month and year from A SAS Date Value
  • ✔ Extract, Edit and Search Character Variable Values

SAS PROCEDURES:

  • ✔ Specify SAS Data Sets to Print
  • ✔ Select Variables and Observations to Print
  • ✔ Specify Column totals for Numeric Variables
  • ✔ Sort Data by Values of One or more Variables
  • ✔ Assign Descriptive Labels to Variables
  • ✔ Double Space SAS Listing Output
Append Procedure Plot Procedure
Compare Procedure Print Procedure
Contents Procedure Datasets Procedure
Export Procedure Format Procedure
Freq Procedure Import Procedure
Means Procedure Printto Procedure
Report Procedure Sort Procedure
Summary Procedure Tabulate Procedure
Transpose Procedure Univariate Procedure

CREATING LIST REPORTS:

  • ✔ The Variables to Appear in your Table
  • ✔ The Statistic to be Computed for Each Variable
  • ✔ The Arrangement of Statistic and Variable in the Table
  • ✔ Additional Features Such as Formats for Values in the Table,Column and Row Totals and Labels for Statistics and Summary Variable
  • ✔ Creating Plots
  • ✔ Creating Vbar, Hbar,Block and Pie Charts
  • ✔ Enhancing Reports
  • ✔ Enhancing and Exporting Charts and Plots
  • ✔ Enhancing your Output with Ods
  • ✔ Using Ods Statements to Create HTML
  • ✔ Using Ods Statements to Create RTF, PDF

Advance SAS

SAS / MACROS

UNDERSTANDING THE CONCEPTS AND FEATURES OF MACRO PROGRAMMING:

  • ✔ What is SAS Macro Facility?
  • ✔ What are the Advantages of Sas Macro Facility?
  • ✔ Where can the Sas Macro Facility be Used?
  • ✔ Examples of the SAS Facility
  • ✔ Comparing Macro Language Processing and SAS Language Processing
  • ✔ Processing a SAS Program that Contains Macro Language

MACRO PROGRAMS:

  • ✔ Creating Macro Programs
  • ✔ Executing a Macro Program
  • ✔ Passing Values to a Macro Program through Macro Parameters

MACRO EXPRESSION AND MACRO PROGRAMMING STATEMENTS:

  • ✔ Constructing Macro Expression
  • ✔ Conditional Processing with the Macro Language
  • ✔ IterationProcessing with the Macro Language
  • ✔ Branching in Macro Processing

MACRO VARIABLE:

  • ✔ Basic Concept of Macro Variable
  • ✔ Referencing Macro Variables
  • ✔ Understanding Macro Variables
  • ✔ Displaying Macro Variable Values
  • ✔ Understanding Automatic Macro Variables
  • ✔ Understanding Userdefined Macro Variables
  • ✔ Combining Macro Variables with Text
  • ✔ Referencing Macro Variables Indirectly

MACRO LANGUAGE FUNCTIONS:

  • ✔ Macro Character Functions
  • ✔ Macro Evaluation Functions
  • ✔ Macro Quoted Functions

APPLYING YOUR KNOWLEDGE OF MACRO PROGRAMMING:

  • ✔ Storing and Reusing Macro Programs
  • ✔ Debugging Macro Programming
  • ✔ Understanding the types of Error that can occur in Macro Programming

SAS / SQL

INTRODUCTION TO THE SQL PROCEDURE:

  • ✔ What is SQL?
  • ✔ Terminology
  • ✔ Comparing Proc SQL with SAS Data Step

CREATING AND UPDATING TABLES

  • ✔ Creating Tables
  • ✔ Inserting Rows into Tables
  • ✔ Updating Data Values in Table
  • ✔ Deleting Rows
  • ✔ Altering Columns
  • ✔ Deleting a Table
  • ✔ Using SQL Procedure tables in SAS Software
  • ✔ Using PROC SQL with the SAS MACRO Facility
  • ✔ Creating and Using MACRO Variables in SQL

RETRIEVING DATA FROM A SINGLE TABLE

  • ✔ Overview of the Select Statement
  • ✔ Selecting Columns in Table
  • ✔ Creating New Columns
  • ✔ Sorting Data
  • ✔ Retrieving Rows that Satisfy a Condition
  • ✔ Summarizing Data
  • ✔ Grouping Data
  • ✔ Filtering Grouped Data

SAS AND SDTM PROJECTS

  • ➔ Data Validation Programming
  • ➔ SDTM Mapping Programming Using SAS
  • ➔ TABLES,LISTING & GRAPHS (Statistical Programming)
  • ➔ SDTM Annotation on CRF
  • ➔ SDTM Mapping Specifications
  • ➔ Developing Define Document (Metadata)

ADAM(Analysis Data Model)

➔ ADAM Specifications

➔ ADAM Projects