The Simplest Guide to Clinical Trials Data Analysis with SAS

Name: The Simplest Guide to Clinical Trials Data Analysis with SAS
Rating: 4.3 (1622 reviews)

Created byAslam Khan

Last updated 12/2024

English

What you'll learn

Get introduced to the Life Science/ Pharmaceutical industry in simple, visual pictures
Learn the fundamental concepts of Clinical Drug Development / Clinical Trials processes
Understand the various Phases of Clinical Trials in the context of SAS programming
Get introduced to the various clinical study documents like Protocol, Statistical Analysis Plan etc.
Understand raw data and how it is collected, stored, analysed and reported
Work hands-on with sample study data that you will import, prepare, restructure and visualize
Generate an actual Clinical Study Reports from the derived data you will create
See for yourself how SAS programming is an integral part of putting a drug into the market
A guide to the SAS Certified Clinical Trials Programmer Using SAS®9 Certification Exam

Course content

4 sections • 37 lectures • 2h 3m total length

Course Overview1:21
Explore three modules on clinical trials data analysis with SAS, covering industry context, protocol and statistical analysis plan, inclusion and exclusion criteria, and building clinical study reports for regulatory submission.
Download the eBook and Course Slides0:29
Components of the Pharma/ Life Science Industry4:39
Phases of Clinical Trials5:41
Explore the two main clinical trial paths, from preclinical lab and animal testing to human phased trials. Learn safety, efficacy, and regulatory steps like NDA and FDA approval.
Data and Reports in Clinical Trials3:55
Types of data in Clinical Trials4:34
Explore the data types in clinical trials, including adverse events, vital signs, lab data, and EKGs, and how randomization and exposure data feed final SAS deliverables.
Section Conclusion0:39
Clinical Trial Fundamentals

Get to know the Clinical Study Documents - Section Overview0:39
Study Documents - The Clinical Study Protocol2:10
Identify key study documents guiding SAS programming in clinical trials, with the protocol as the central plan. See how sponsors and IRBs review safeguards for participant safety and study integrity.
The Informed Consent1:08
The Inclusion- Exclusion Criteria0:35
The Statistical Analysis Plan (SAP), mock shells, and Case Report Forms (CRFs)3:38
Get to know Clinical Study Documents - Section Conclusion0:10
Review the importance and purpose of clinical study documents and how they support the analysis and reporting of clinical trials.
Clinical Study Documents

Building the CSRs - Section Overview1:04
SAS OnDemand Registration3:22
Logging-in to SAS after registration0:54
General SAS Programming Steps for building any CSRs2:14
Understanding the Demographics Case Report Form (CRF)4:17
Learn how to transform CRF data into derived datasets and import them into SAS to generate the demographics table, a foundational clinical study report.
Understanding the Demographics Table3:18
Construct a demographics table from raw data by linking age, sex, race, and TT to derive variables, producing a SAS-driven clinical study report table with placebo and active groups.
Planning to program the Demographics Table5:11
Importing raw Demographics data into SAS3:13
Importing raw data into SAS
Building the Demographics table
Deciding which PROCs to use1:43
Deriving the AGE variable10:13
Deriving the AGE variable
Obtaining Summary Statistics for AGE3:37
Adding the 3rd Treatment Group using Explicit Output5:21
Procedures and Variables
Deriving the SEX variable3:21
Obtaining Summary Statistics for SEX3:08
Use the following PROC FREQ to use the percentage row count variable called PCT_ROW, not the PERCENT variable which is the cell count percentage.
proc freq data=demog2 noprint ;
table trt*sex/ outpct out =genderstats;
run;
Summarizing Data
Concatenating the COUNT and PERCENT variables2:51
Deriving the RACE variable2:47
Obtaining Summary Statistics for RACE2:55
Use the following PROC FREQ to use the percentage row count variable called PCT_ROW, not the PERCENT variable which is the cell count percentage.
proc freq data=demog2 noprint ;
table trt*race/ outpct out =racestats;
run;
Stacking all 3 Summary Statistics together5:42
Fixing the precision points3:53
Fix precision points and missing parentheses in SAS code by applying conditional formatting: N zero decimals, mean/min/max one decimal, std two decimals, and increase value length.
Transposing data2:44
Explore transposing a vertically arranged all stats dataset into a three-column table using proc transpose, aligning placebo, active, and overall patients with by, id, and underscore prefix options.
Structuring Data
Fixing the order of statistical parameters5:05
Building the final report1:51
Putting the final touches to the report10:39
Refine a SAS clinical trial report by using Proc SQL and Proc Report to add labels, population counts, macro variables, titles, and footnotes for the final demographics table.
Final Report
Building the CSRs - Section Conclusion0:33
Order your course completion certificate after you have completed this training (all lectures, quizzes, assignments and practice exams). See instructions on the last page of Resource Guide eBook.
Final Test

Requirements

Basic SAS Programming
No prior Pharmaceutical experience is necessary
Internet connectivity for working in the SAS Studio Edition using SAS OnDemand (no installation necessary)

Description

This course gives an introduction to the Pharmaceutical/ Life Science industry in a simple and visual style that is easy to understand. It shows how SAS is used as a tool to work with the vast amount of clinical data within this industry. The course takes you through an example clinical study sample data, and generate various Clinical Study Reports that are submitted to the FDA (in the US) or other regulatory authorities in other countries. You will not only hone your SAS programming skills but will also learn essential concepts needed to work in the Pharma industry in the areas of Biostatistics and Clinical Data Management.

After the introduction to the pharma industry and learning relevant concepts about Clinical Trials, the course takes you through a hands-on training exercise to build the very important and fundamental Clinical Study Report called the Demographics Table.

You will begin with a sample clinical study data in an Excel sheet, then you will import it into SAS, derive all necessary variables as shown in the mock table, and finally generate a clinical study report. All this will be done using guided SAS Programming steps with detailed explanations at every step of programming. At the end of this course, you will have learnt to work with Clinical Study Data, generate a real Clinical Study Report, and extend those steps to build other reports that constitute Clinical Trial submissions to the regulatory bodies.

Prerequisites: You will need basic SAS programming knowledge to work with code discussed in this course. You can take my course on SAS programming ("The Simplest Guide to SAS Programming") available on Udemy.

A guide to the following SAS certification exam:

SAS Certified Clinical Trials Programmer Using SAS 9

Earn a Certificate

When you finish listening to all videos, assignments, quizzes and practice exams, you'll earn a Certificate that you can share with prospective employers and your professional network.

Who this course is for:

Anyone wanting to get into the Life Science / Pharmaceutical industry and looking to work in this field
Want to take up a job as a Clinical SAS Programmer in a Pharma company or a CRO (Contract Research Org.)
Want to just play with data using the SAS Programming concepts

The Simplest Guide to Clinical Trials Data Analysis with SAS

What you'll learn

Explore related topics

Course content

Introduction7 lectures • 21min

Get to know the Clinical Study Documents6 lectures • 8min

Building the Clinical Study Reports (CSR)24 lectures • 1hr 30min

Capstone Project0

Requirements

Description

Who this course is for: