Overview

The Clinical SAS Programming Training course is designed to equip participants with foundational and advanced skills in SAS programming, data analysis, and reporting tailored for the clinical research and pharmaceutical industries. This comprehensive program covers key topics such as SAS programming fundamentals, clinical trial data standards (CDISC), statistical analysis, and the creation of clinical trial reports and graphs. Participants will gain hands-on experience in managing clinical data, adhering to regulatory requirements, and preparing for careers in clinical data management and analysis. 

Target Audience

  • Professionals aspiring to enter the field of clinical SAS programming 
  • Life sciences graduates seeking opportunities in clinical research and biostatistics 
  • Clinical Research Associates (CRAs), data analysts, and biostatisticians 
  • Healthcare professionals transitioning to clinical data management roles 
  • Professionals working in pharmaceutical, biotechnology, or Contract Research Organizations (CROs) 

Prerequisites

  • A background in life sciences, statistics, computer science, or a related field is recommended 
  • Basic understanding of programming concepts is beneficial but not required 
  • No prior experience in SAS or clinical trials necessary 

Curriculum

Regulatory Documents

  • ICH GCP – E3, E6, E8 Guidelines 
  • 21 CRF PART 11 
  • CDISC – CDASH, SDTM, ADAM, Define.xml 

Study Level documents

  • Protocol, SAP, CRF, ACRF 
  • EDC database, About RAW data 

Dictionaries & Versions

  • MEDDRA / WHODDrug 
  • Overview of Clinical Trails 
  • Drug development phases  
  • PreClinical, phase 1 to 4, IND, NDA approvals, Ethics committee 
  • Objectives (Primary, Secondary), End points (Primary, Secondary) 
  • SAS software introduction, web application, create student account, setup 
  • SAS introcution, uses in diffferent domains/sectors 
  • Different tabs in SAS softeware and its importance- Code, Log, Ouput, files 
  • About PDV concept 
  • Accessing data – Libraries, storage folders, Datasets, Variables, Columns 
  • libname statement 
  • filename statement 
  • infile statement – to read external data into sas 
  • Dictionary.vcolumn 
  • Dictionary.tables 
  • Creating SAS Data Sets – Data steps/proc steps 
  • Understanding DATA Step Processing 
  • SET, KEEP, DROP, RENAME statements 
  • SAS Language Errors – Identifying and Correcting them 
  • SAS libraries – Default (work) & User defined. SASHELP.Class, Car’s datasets 
  • SAS naming conventions for Library, Dataset, Variable
 

Using Functions to Manipulate Data

  • Mathematical – ABS, LOG, SUM, MIN, MAX, AVG, STD, count 
  • Character – cat, compress, strip, left, trim, scan, substr, compbl, lowcase, upcase, propcase, tranwrd, translate, index, find 
  • Date & time – today, time, mdy, intck 
  • Truncation – round, ceil, floor 
  • Other – input, put, length, cmiss, nmiss, n, lag 
  • Statements – label, Sum, Keep, drop, rename, output, length, format, put, input, options, title, footnotes 
  • Options – Keep, drop, rename, label, 
 

Filtering data & conditional flag/output 

  • WHERE 
  • IF condition 
  • IF – THEN condition 
  • Where VS IF 

DO Loops

  • DO loops – nested do-loop – creating dummy datasets 
  • ARRAYS with DO loops 
 

Combining SAS Data Sets

  • with SET statement 
  • with MERGE statement 
  • one-to-one or one-to-many merging 
 

Creating Reports / Creating Outputs

  • data _NULL_; 
  • Proc print and ODS system (.rtf,.pdf,.xls) 
  • Proc contents 
  • Proc sort 
 

BY-Group Processing

  • SUM/RETAIN statement 
  • FRIST.VAR and LAST.VAR variables. 
 

Types of Statistics   

  • Discritive – data is summarised through the given observations 
  • Inferential – used to interpret the meaning of Descriptive statistics(p-value) 
  • and used to compare the differences between the treatment groups. 
  • proc append, SET statement 
  • Proc report 
  • proc freq 
  • proc means/summary 
  • proc univariate 
  • proc format, informat proc transpose 
  • Proc Tabulate 
  • proc import 
  • proc export 
  • proc glm 
  • proc t test 
  • proc corr 
  • proc chart 
  • proc plot 
  • Proc compare 
 

Advance SAS topics

  • Macro definition, uses 
  • Parameters – keyword, positional 
  • Creating macro var using diff. ways 
  • Example with data steps, Do loops & PROCs 
  • PROC SQL 
  • JOINS 
  • Flags creation 
  • apply conditions 
  • Calculations 
  • Functions 
 

Domain  

SDTM v3.2

  • Introduction, mapping specifications 
  • Types of Domains/classes 

Types of flags

  • Trial Domains 
  • DM 
  • AE 
  • CM 
  • VS 
  • LB 
 

ADAM v1.0

  • ADAM IG for introduction 
  • Mapping Specification 
  • Types of Domains/classes, Complex derivations 
  • ADSL, common/core vars, Derivations like study day 
  • ADAE 
  • ADVS  

Introduction, Mockshells, stats team 

Tables

  • Demographic  
  • Ae summary 
  • cm summary 
  • VS table 

Listings

  • Demographic  
  • Ae summary 
  • cm summary 

Figures

  • About Clinical SAS industry 
  • different SAS Roles/designations 
  • edit checks team/clinical sas team 
  • bio stats team 

Roles in SAS Programming

  • Developer 
  • Validator 
  • Reviewer (Manager/Senior Programmer) 
  • Issue logs (for Raw, SDTM, ADAM, TFLs) 
  • Different types of analysis 
  • Study Delivery timelines 
  • Pinnacle 21 
  • USFDA submission docs – SDRG, ADRG, Define 
 

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Features

Real Life Case Studies

Projects modeled on select use cases with implementation of diverse technology concepts

Assignments

All guided classes and courses are mandatorily followed by useful practical assignments

24x7 Expert Support

Every technical query is resolved on demand with readily available expert assistance

Instructor-led Sessions

Technical session conducted under the guidance of qualified and certified educationists

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