SAS Clinical

SAS (Statistical Analysis System) is a software suite developed by SAS Institute for advanced analytics, multivariate analyses, business intelligence, data management, and predictive analytics.
SAS was developed at North Carolina State University from 1966 until 1976, when SAS Institute was incorporated. SAS was further developed in the 1980s and 1990s with the addition of new statistical procedures, additional components and the introduction of JMP. A point-and-click interface was added in version 9 in 2004. A social media analytics product was added in 2010.
SAS data can be published in HTML, PDF, Excel and other formats using the Output Delivery System, which was first introduced in 2007. The SAS Enterprise Guide is SAS' point-and-click interface. It generates code to manipulate data or perform analysis automatically and does not require SAS programming experience to use.
The SAS software suite has more than 200 components Some of the SAS components include:

Base SAS – Basic procedures and data management
SAS/STAT – Statistical analysis
SAS/GRAPH – Graphics and presentation
SAS/OR – Operations research
SAS/ETS – Econometrics and Time Series Analysis
SAS/IML – Interactive matrix language
SAS/AF – Applications facility
SAS/QC – Quality control
SAS/INSIGHT – Data mining
SAS/PH – Clinical trial analysis
Enterprise Miner – data mining
Enterprise Guide - GUI based code editor & project manager
SAS EBI - Suite of Business Intelligence Applications
SAS Grid Manager - Manager of SAS grid computing environment
WHY SAS IN CLINICAL TRIALS?
With the primary focus of a biopharmaceutical company or a CRO being science and research, they need a versatile technology organization with clinical research expertise to take care of all their data management, clinical programming and IT needs without incurring additional fixed costs. They also look for supporting partners who need to be responsive and can ramp up and down to meet the peaks and valleys of work load, at a reasonable cost while ensuring high quality working in regulated environments.

CONTENTS
Introduction to drug discovery and development process
Overview of highly regulated drug development process, from discovery to bringing a biopharmaceutical product to market.
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, etc.)
Introduction to Clinical Trial Data
Learn to prepare and clean clinical trial data
Know how to categorize and summarize clinical data
Studying and classifying different types of clinical trial data {Safety (ISS) and Efficacy (ISE) Data}
Getting acquainted with new Clinical Data Interchange Standards Consortium (CDISC)
Implementation in categorizing clinical data.
Using SAS to Create Analysis Data sets
Key concepts for creating and transforming analysis data sets (Using DATA steps and PROC TRANSPOSE)
Comparing Data sets using PROC COMPARE
Understanding and creating Time-to-Event, Change-from-Baseline, Critical variables data sets.
Generate Customized Clinical Trials Tables, Listings and Graphs/Figures
Using PROC TABULATE to create clinical trial tables
Using PROC REPORT to report clinical trials tables and listing
Creating summaries of Adverse Event, Concomitant medication, Laboratory data using DATA steps and various SAS Procedures
Creating Kaplan-Meier Survival Tables using PROC LIFETEST or PROC GPLOT
Using ODS with PROC REPORT and PROC TABULATE to generate nice looking tables and Listings.
Generating Graphs and Plots using SAS/BASE, SAS STAT and SAS/GRAPH
Producing Bar and Pie charts using PROC GPLOT and PROC GCHART
Creating Box and Scatter Plot using PROC BOXPLOT, PROC GPLOT and PROC UNIVARIATE
Performing Common Analyses and Obtaining Statistics
Obtaining Descriptive Statistics
Obtaining Inferential Statistics from Categorical Data
Analysis
Obtaining Inferential Statistics from Continuous Data
Analysis
Obtaining Time-to-Event Analysis Statistics
Exporting Data
Using the SAS XPORT Transport Format
Creating XML Files

Last modified: Friday, 12 August 2016, 4:23 AM