Clinical SAS offers young and emerging professionals in fields like pharmaceuticals, clinical research, and biotechnology the opportunity to significantly advance their careers and professional goals and deploy their knowledge of SAS programming and the different tools and products provided by the SAS Institute to analyze, transform, manage, and report the data generated in clinical trials and collate and present them in a cohesive and comprehensive manner that adheres to the guidelines and protocols of various statutory bodies and institutions, after robust statistical testing and analysis, scientific procedures and following the procedures and norms as prescribed by the presiding bodies that offer clearances and patents.

Course content

Introduction

• Introduction of SAS software.
• Industries using SAS
• Components of SAS System.
• Architecture of SAS system.
• Functionality of SAS System.
• Introduction of SAS windows

Working in the SAS Environment

• Functionality of SAS Windows.
• Creating and managing SAS Libraries.
• Overview of SAS Data states.
• Types of Libraries.
• Storing files temporarily and permanently.
• Referencing SAS files.

Creation database from raw data

• Steps to create a SAS dataset.
• Creating SAS dataset using text file.
• Creating SAS dataset using text file with delimiters.
• Creating SAS dataset using structured text file.
• Creating SAS dataset using unstructured text file.
• Creating SAS dataset using Excel file.
• Creating SAS dataset using Access file.
• Creating SAS dataset using values inside the code.

Output delivery system

• Concepts of output delivery system.
• How ODS works and viewing output of ODS in different format.
• HTML, RTF, PDF etc..

Combination the dataset

• One-o-one reading
• One to many
• Many to many
• Concatenation
• Interleaving,
• Match merge

Functions

• Character function
• Numerical function
• Arithmetical function
• Mathematical function
• Date Function

Loops in SAS: Do Loops

• Do Loop
• Do While
• Do Until

Array

• Definition of array
• Example of array

PROCEDURES

• Procedure Format.
• Procedure Contents.
• Procedure Options.
• Procedure Append.
• Procedure Compare.
• Procedure Transpose.
• Procedure Print.
• Procedure Import.
• Procedure Export.
• Procedure Datasets.
• Procedure Tabulate.
• Procedure Chart, Gchart, Gplot.
• Procedure Report.

GRAPHS

• Introduction to graphics.
• Introduction to graphics.
• Types of Graphics (with latest models)
• Defining procedure Graphics.

 ProcSql 

• Generate detail reports by working with a single table, joining tables, or using set operators in the SQL procedure.
• Generate summary reports by working with a single table, joining tables, or using set operators in the SQL procedure.
• Construct sub-queries and in-line views within an SQL procedure step.
• Compare solving a problem using the SQL procedure versus using traditional SAS programming techniques.

 Macro

• Create and use user-defined and automatic macro variables within the SAS Macro Language.
• Automate programs by defining and calling macros using the SAS Macro Language.
• Understand the use of macro functions.

 Introduction of SAS and Clinical research

• SAS role in Clinical Research.
• What is Clinical trial?
• What is Protocol and role of Protocol in Clinical Research?
• Which is playing main role in Clinical Research?

Creation and Validation of SDTM &ADaM

• CDISC overview
• SDTM overview – Part I and Part II
• ADaM introduction
• SDTM &ADaM Assignments
• CRF Annotation
• SDTM- Mapping specs creation
• SDTM- Dataset Development
• SDTM- Dataset Validation
• ADaM- Mapping specs creation
• ADaM- Dataset Development

 Introduction to drug discovery and development process

• Understanding major phases (Phase I – IV) of clinical trials and clinical data
• management
• Food and Drug Administration (FDA) regulations and Guidance (21 CFR part 11, GCP,
• eCTD)
• Regulatory overview and approval process including IND/NDA to FDA
• Types and parameters of Clinical trial
• Getting in depth knowledge about the functional group and working of
• CRO/Pharmaceutical industry and knowing in and out of guidelines pertaining to
• company involved in clinical trials
• Learning about the general department structure of pharmaceutical industry, roles
• and responsibilities of SAS programmer in the company
• Understanding clinical study and documents {e.g. Protocols, Case Report Form (CRF),
• annotated and electronic Case Report Form (aCRF and eCRF), Statistical Analysis Plan
• (SAP)}
• Learning more about types of analysis in clinical trials (Pharmacokinetic,
• Pharmacodynamics, Efficacy, Safety, )

 Clinical Trials Data Structures

• Identify the classes of clinical trials data (demographic, lab, baseline, concomitant medication, etc.).
• Identify key CDISC principals and terms.
• Describe the structure and purpose of the CDISC SDTM data model.
• Describe the structure and purpose of the CDISC ADaM data model.
• Describe the contents and purpose of define.xml.

Transform Clinical Trials Data

• Apply categorization and windowing techniques to clinical trials data.
• Transpose SAS data sets.
• Apply ‘observation carry forward’ techniques to clinical trials data (LOCF, BOCF, WOCF).
• Calculate ‘change from baseline’ results.

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