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SAS Clinical

As the most complete software for all the needs in data manipulation and data analysis in every aspect, SAS is used as data processing tool by many companies, especially large corporations, where huge amount of data is analyzed.

Course Details

Defining the lecture scenario

  • Introduction to SAS programs (Components, Characteristics, Layout, and Processing of SAS Programs)
  • Exploring SAS Windowing Environment
  • identifying the three primary SAS programming windows
  • navigating SAS programming windows
  • editing and executing SAS code
  • saving and retrieving SAS code
  • using the SAS Help facility
  • Explaining the concept of a SAS data library
  • How SAS files are stored
  • Creating temporary or permanent libraries
  • Understanding SAS data sets
  • Overview of data sets
  • Data types and size of SAS data sets
  • Observations (Rows) and Variables (Columns)
  • Missing values
  • Rules for SAS names
  • Methods for getting data into SAS
  • Reading raw data (text, ASCII, CSV, Exceland flat files) into SAS and converting it to SAS dataset

Part 2: Using SAS DATA steps

  • Creating SAS data set using DATA steps
  • Creating and Modifying variables
  • Associating and changing SAS variable attributes
  • Access Specifiers
  • Executing statements conditionally (If-then-else)
  • Dropping and Keeping variables in a dataset
  • Understanding DATA step processing
  • Finalize, Dispose & Garbage collectors
  • My Base, my class & my keywords

Working with SAS Data

  • Using and Selecting SAS functions (PUT, INPUT, MIN, MAX, SUM, UPCASE, etc.)
  • Working with SAS formats and informats
  • Understanding SAS dates

Part 3: Getting Acquainted with SAS PROCEDURES

  • Using SAS procedures
  • Getting started with the PROCPRINT
  • Sorting and Grouping observations using PROC SORT
  • Creating user defined formats using PROC FORMAT
  • Summarizing data using PROC MEANS
  • Counting data with PROC FREQ
  • Producing table using PROC TABULATE and PROC REPORT
  • Transposing data with PROC TRANSPOSE
  • Subsetting in Procedures using WHERE statement

Part 4 : Output Delivery System (ODS)

  • Concepts of Output Delivery System and it’s usefulness in generating SAS outputs
  • Select and trace procedure output for selective listings
  • Using ODS to create HTML, PDF, RTF and PRINTER output
  • Customizing ODS output using STYLE and PROC TEMPLATE option
  • Generate summary tables using ODS RTF and PROC REPORT

Part 5: Using SAS Macro Facility

  • Macro concepts
  • Substituting Text with Macro variables
  • Adding different parameters to Macros
  • What are the advantages of the SAS Macro facility
  • Writing data driven programs with CALL SYMPUT
  • Understanding automatic and user-defined macro variables

Part 6: Introduction to Drug Development Process in Pharmaceutical Industry

  • 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
  • Learning rationale for each phases of drug development cycle and introducing role of SAS programmer in each phase
  • 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 trials

  • Learning about the general department structure of pharmaceutical industry, roles and responsibilities of SAS programmer in the company
  • Getting to know what Standard Operating Procedures (SOP’s) and Guidelines are and its importance
  • Discussing and Reviewing sample SOP’s and Guidelines from a real pharmaceutical industry
  • Understanding clinical study and documents {e.g. Protocols, Case Report Form (CRF), annotated and electronic Case Report Form (aCRF and eCRF), Statistical AnalysisPlan (SAP)}
  • Get a feel of folder structure adopted by most of the pharmaceutical and CRO companies
  • Learning moreabout types of analysis in clinical trials (Pharmacokinetic, Pharmacodynamics, Efficacy, Safety, etc.)

Part 7: 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 InterchangeStandards Consortium (CDISC) implementation in categorizing clinical data
  • Working with real pharmaceutical industry data (demographics, concomitant medication, medical history, laboratory data, adverseevent, end point data, etc.)

Part 8: 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
  • Learning about use of Medical Dictionaries (MedDRA and WHO Drug) in generating Adverse Event dataset
  • Understanding and creating Time-to-Event, Change-from-Baseline, Critical variables data sets

Part 9: 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

ASP .NET INTRODUCTION

  • How is ASP .net different from ASP
  • ASP .NET design goals
  • Development environment for ASP .NET application
  • Identifying the features of ASP .NET
  • Identifying programming modules in ASP .NET
  • Web forms
  • Web services

Generating Graphs and Plots using SAS/BASE, SAS STAT and SAS/GRAPH

  • Processing of web pages
  • Server control hierarchy
  • Web controls
  • Buttons, list controls, text boxes, hyper links
  • HTML controls
  • HTML anchor, button

STRUCTURE OF AN ASP .NET PAGE ASP .NET PROGRAMMING VALIDATION CONTROLS

  • Producing Bar and Pie charts using PROC GPLOT and PROC GCHART
  • Creating Box and Scatter Plot using PROC BOXPLOT, PROC GPLOT and PROC UNIVARIATE
  • Creating Kaplan-Meier Plot using PROC GPLOT or PROC LIFETEST

Part 10: Resume Workshop

  • Consultantswill have opportunity to write and develop resume in this workshop. Sample resumes from experience SAS Consultants will be shared. They will be instructed on skills sets that must be listed on there resumes. Every consultant’s resume will be reviewed by expert personally before sending it out for marketing