SAS Clinical Trial Data Analytics
- 24 weeks
- 144 hours
The SAS Clinical Trial Data Analytics course delivers practical skills in SAS programming and clinical data analysis, equipping you for success in clinical research and regulatory compliance.
Course Overview
SAS Clinical Trial Data Analytics is a specialized course designed to provide in-depth knowledge of analyzing clinical trial data using SAS software. It covers essential topics like data management, statistical analysis, and reporting, equipping participants with the skills needed to work in clinical research and healthcare industries.
Advantage
The SAS Clinical Trial Data Analytics course equips participants with industry-relevant skills in managing, analyzing, and reporting clinical trial data using SAS, the leading software in the field. With a comprehensive curriculum and hands-on experience, learners gain practical expertise that enhances their career opportunities in clinical research, pharmaceutical companies, and regulatory agencies. The course prepares students for high-demand roles in clinical data management and ensures they are well-versed in meeting industry standards for data accuracy and regulatory compliance, culminating in a professional certification.
What you'll learn
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Base and Advanced SAS for clinical trial data analytics
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Analysis and reporting using SAS software
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Specialized modules: ADaM, TLF, SDTM
- Components of the SAS System
- Data-Driven Tasks
- Turning data into Information
- Introducing to SAS Programs
- Running SAS Programs
- Mastering Fundamental Concepts
- Diagnosing and Correcting Syntax Errors
- SAS Data Libraries
- Getting Started with the PRINT Procedure
- Sequencing and Grouping Observations
- Identifying Observations
- Special WHERE Statement Operators
- Customizing Report Appearance
- Formatting Data Values
- Creating HTML Reports
- Reading Raw Data Files: Column Input
- Reading Raw Data Files: Formatted Input
- Examining Data Errors
- Assigning Variable Attributes
- Changing Variable Attributes
- Reading Excel Spreadsheets
- Reading SAS Data Sets and Creating Variables
- Conditional Processing
- Dropping and Keeping Variables
- Reading Excel Spreadsheets Containing Date Fields
- Concatenating SAS Data Sets
- Merging SAS Data Sets
- Combining SAS Data Sets: Additional Features
- Introduction to Summary Reports
- Basic Summary Reports
- The Report Procedure
- The Tabulate Procedure
- Producing Bar and pie Chart
- Enhancing output
- Producing Plots
- Overview
- Review of SAS basics
- Review of DATA Step Processing
- Review of Displaying SAS Data Sets
- Working with Existing SAS Data Sets
- Outputting Multiple Observations
- Writing to Multiple SAS Data Sets
- Selecting Variables and Observations
- Writing to an External File
- Creating an Accumulating Total variable
- Accumulating Totals for a Group of Data
- Reading Delimited Raw Data Files
- Controlling When a Record Loads
- Reading Hierarchical Raw data Files
- Introduction
- Manipulating Character values
- Manipulating Numeric values
- Manipulating Numeric values based on Dates
- Converting variable Type
- Using the PUT Statement
- Using the DEBUG Option
- Do Loop Processing
- SAS Array Processing
- Using SAS Arrays
- Match-merging Two or more SAS Data Sets
- Simple Joins Using the SQL Procedure
- Setting Up for the Course
- What Is SQL?
- Introduction to the SQL Procedure
- Demonstration: Exploring the customer Table
- Generating Simple Reports
- Summarizing and Grouping Data
- Creating and Managing Tables
- Using DICTIONARY Tables
- Introduction to SQL Joins
- Inner Joins
- Outer Joins
- Complex Joins
- Performing a Reflexive Join
- Subquery in WHERE and HAVING clauses
- In-Line Views (Query in the FROM Clause)
- Subquery in the SELECT Clause
- Introduction to Set Operators
- INTERSECT, EXCEPT, and UNION
- OUTER UNION
- Creating User-Defined Macro Variables
- Creating Data-Driven Macro Variables with PROC SQL
- Overview of SAS/ACCESS Technology
- SQL Pass-Through Facility
- Demonstration: Using an SQL Pass-Through Query
- SAS/ACCESS LIBNAME Statement
- Demonstration: Using the SAS/ACCESS LIBNAME Statement
- FEDSQL Procedure
- Why SAS Macro?
- Setting Up for This Course
- Solutions
- Program Flow
- Creating and Using Macro Variables
- Solutions
- Macro Functions
- Using SQL to Create Macro Variables
- Using the DATA Step to Create Macro Variables
- Indirect References to Macro Variables
- Solutions
- Defining and Calling a Macro
- Macro Variable Scope
- Conditional Processing
- Iterative Processing
- Solutions
- Storing Macros
- Generating Data-Dependent Code
- Validating Parameters and Documenting Macros
- Solutions
- Overview of drug development phases
- Roles and responsibilities in drug development
- Importance of data management in drug development
- Regulatory authorities and their roles
- New drug application (NDA) process
- Generic drug approval process
- Biologics license application (BLA) process
- Phases of clinical trials
- Study design and protocol development
- Patient recruitment and enrollment
- Data collection and management in clinical trials
- Purpose and benefits of CDISC standards
- Overview of CDISC models: SDTM, ADaM, ODM
- Importance of data standards in clinical research
- What is SDTM?
- Observations and variables in SDTM
- Special purpose datasets
- General observation classes in SDTM
- Introduction to SDTM domain models
- Special purpose domains: DM, CO, SE, SV
- Interventions: CM, EX, SU, EC
- Events: AE, DS, MH, DV, HO
- Findings: LB, EG, VS, PE, IE, DD, QS
- Trial design domains: TA, TE, TS, TI, TV
- Supplemental qualifiers domains and RELREC
- SDTM mapping programming using SAS
- Real-time project on SDTM
- SDTM annotation on CRF
- Purpose and significance of ADaM
- Key concepts in ADaM
- ADaM naming conventions
- ADaM implementation process
- Fundamentals of ADaM standards
- Variables in general
- ADSL variables
- BDS variables
- Real-time project on ADaM
- ADSL domain
- ADAE domain
- ADVS domain
- Generating summary reports
- Introduction to ICH E6, E9, and E3 guidelines
- Protocol and CRF/eCRF
- Statistical analysis plan (SAP)
- Mock shells
- Introduction to the clinical study report
- SAS program development and validation (QC)
- Generating listings and graphs
Admission Process
Please call to admission counselor for course fees, registration fees, EMI fecilities,registration form and other formalities. Contact to admission counselor
+91-9830247087
Who Can Join?
Any graduate with knowledge of basic computing.
Requirment
1. Personal computer/laptop with webcam and microphone
2. Stable internet connections
Payment Details
Bank Details:
KLMS HANDS-ON SYSTEMS PRIVET LIMITED
Account Number: 19700200000420
IFSC Code: BARB0SALTLA (5th letter is numeric zero)
UPI Payment: 9432257052@okbizaxis
- Live Instructor-Led Course
- Project and Case Studies
- Certificate of completion
- Learn from Experts
- Placement Assistance
