The Simplest Guide To Clinical Trials Data Analysis With Sas

Step into the world of Pharmaceutical industry |Clinical Trials |Clinical Research |Biostatistics |Data Management| SAS
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
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
Overview
Section 1: Introduction
Lecture 1 Course Overview
Lecture 2 Components of the Pharma/ Life Science Industry
Lecture 3 Phases of Clinical Trials
Lecture 4 Data and Reports in Clinical Trials
Lecture 5 Types of data in Clinical Trials
Lecture 6 Section Conclusion
Section 2: Get to know the Clinical Study Documents
Lecture 7 Get to know the Clinical Study Documents - Section Overview
Lecture 8 Study Documents - The Clinical Study Protocol
Lecture 9 The Informed Consent
Lecture 10 The Inclusion- Exclusion Criteria
Lecture 11 The Statistical Analysis Plan (SAP), mock shells, and Case Report Forms (CRFs)
Lecture 12 Get to know Clinical Study Documents - Section Conclusion
Section 3: Building the Clinical Study Reports (CSR)
Lecture 13 Building the CSRs - Section Overview
Lecture 14 SAS OnDemand Registration
Lecture 15 Logging-in to SAS after registration
Lecture 16 General SAS Programming Steps for building any CSRs
Lecture 17 Understanding the Demographics Case Report Form (CRF)
Lecture 18 Understanding the Demographics Table
Lecture 19 Planning to program the Demographics Table
Lecture 20 Importing raw Demographics data into SAS
Lecture 21 Deciding which PROCs to use
Lecture 22 Deriving the AGE variable
Lecture 23 Obtaining Summary Statistics for AGE
Lecture 24 Adding the 3rd Treatment Group using Explicit Output
Lecture 25 Deriving the SEX variable
Lecture 26 Obtaining Summary Statistics for SEX
Lecture 27 Concatenating the COUNT and PERCENT variables
Lecture 28 Deriving the RACE variable
Lecture 29 Obtaining Summary Statistics for RACE
Lecture 30 Stacking all 3 Summary Statistics together
Lecture 31 Fixing the precision points
Lecture 32 Transposing data
Lecture 33 Fixing the order of statistical parameters
Lecture 34 Building the final report
Lecture 35 Putting the final touches to the report
Lecture 36 Building the CSRs - Section Conclusion
Section 4: Final Project
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
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