Unlocking Opportunities: What You Will Learn in SAS Certified Clinical Trials Programming Professional

SAS Programming 1: Essentials

This core module covers the fundamentals of SAS programming, including data steps and procedures (PROC), managing data structures (datasets), and how to manipulate and output data. It will teach you how to create variables and handle missing values ​​using SAS syntax.

SAS Programming 2: Data Manipulation Techniques

This module focuses on advanced data manipulation, merging datasets, using arrays, classifying, and managing large datasets. It includes techniques for summarizing, transposing, and resizing data to meet the needs of clinical trials.

SAS Macro Language 1: Essentials 

In this module, you will learn SAS macro programming, which focuses on automating repetitive tasks and increasing program flexibility. It includes creating and using macro variables and functions to simplify complex programming tasks.

SAS SQL 1: Requirements

In this module, you will understand SQL (Structured Query Language) to query and manipulate clinical trial data in a SAS environment. In this module, you will be able to efficiently extract subsets of data, perform operations, and handle complex queries using SQL.

SAS Report Writing 1: Essentials

In this module, you will learn how to create and format reports using SAS, including creating tables, summaries, and statistical output. You will also learn how to use the Output Delivery System (ODS) to produce high-quality reports in a variety of formats, such as HTML, PDF, and RTF.

SAS/GRAPH: Essentials

This course focuses on using SAS/GRAPH to create visualizations such as bar charts, histograms, pie charts, and scatter plots to effectively represent clinical trial data. You will also learn how to use graphical output to clearly communicate clinical trial results.

Introduction to the Clinical Trial and CRO Industry

This provides an overview of clinical trials, including their structure and phases. It covers the role of Contract Research Organizations (CROs) in the clinical trial process and the specific demands of clinical trial programming.

Hands-on Training on Study Documents

 This part of the training provides practical experience in creating, interpreting, and managing clinical trial study documents, such as protocols and case report forms (CRFs). It covers effective data collection and management according to regulatory standards.

Hands-on Training on CDISC Standards

In this, you will learn to introduce the Clinical Data Interchange Standards Consortium (CDISC), which provides a global standard for clinical trial data.

Analysis Data Model (ADaM) Programming

In this, you will understand how to create and manage analysis datasets that support statistical analysis in clinical trials. You will learn the processes involved in developing ADaM datasets for analysis in clinical trial reporting.

This module focuses on how to structure and manipulate data according to ADaM standards to support clinical trial analysis. It includes creating datasets that facilitate statistical analysis, including basic and advanced statistical methods.

SDTM Programming (Study Data Tabulation Model) 

This module covers how to create datasets in the SDTM format, which is used to submit clinical trial data to regulatory authorities. In this, you will learn how to map raw clinical trial data into the SDTM structure in preparation for regulatory submission.

Hands-on Training on Creating Clinical Trial Reports 

This module will teach you how to create clinical trial reports with tables, lists, and figures (TLFs) based on SAS output. This includes creating comprehensive reports that summarize clinical trial data for analysis, interpretation, and submission.

Hands-on Training on Creating Clinical Trial Graphs

In this module, you will focus on creating effective visualizations (graphs and charts) to represent clinical trial data and results. This includes training with tools and techniques in SAS/GRAPH.

Hands-on training on Define.xml and Reviewer's Guide

In this module, you will learn how to create and manage Define.xml files that provide metadata for clinical trial datasets in CDISC format. You will also learn how to write and format a reviewer's guide with regulatory submissions to explain the dataset and statistical analysis.

Statistics 1: Introduction to ANOVA, Regression, and Logistic Regression

In this module, you will understand the basic statistical techniques used in clinical trials, including ANOVA (analysis of variance), linear regression, and logistic regression. It focuses on applying these methods to clinical trial data to evaluate treatment outcomes and analyze patient responses.

Conclusion:

All of the above modules are designed to provide a comprehensive understanding of SAS programming in the context of clinical trials, covering not only technical skills but also industry standards and regulatory requirements. This includes practical, hands-on training to prepare individuals for the real-world challenges of clinical trial programming and the SAS Clinical Trials Programming Professional Certification Exam.

Throughout the training, assessments assess your understanding of SAS programming and clinical trial standards, ensuring that you are prepared for real-world tasks. This training provides practice and review of key concepts through exercises and assessments that prepare you for the SAS Clinical Trials Programming Professional Certification Exam. The SAS Certified Clinical Trials Programming Professional Course aims to prepare individuals for real-world challenges in clinical research and pharmaceutical data analysis, including SAS programming, CDISC standards, statistical analysis, and clinical trial reporting.