Clinical SAS

Categories: Pharma IT
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About Course

SAS is a software suite that can mine, alter, manage and retrieve data from a variety of sources and perform statistical analysis on it. SAS provides a graphical point-and-click user interface for non-technical users and more through the SAS language.

SAS programs have DATA steps, which retrieve and manipulate data, and PROC steps, which analyze the data. Each step consists of a series of statements.

SAS is widely used in clinical trial data analysis in pharmaceutical, biotech and clinical research companies. SAS programmers play an important role in clinical trial data analysis. 

SAS Clinical /Clinical SAS is the application of SAS technology to clinical domain for clinical trial data analysis in pharmaceutical/biotech and clinical research companies. Familiarity with clinical trial aspects combined with knowledge of SAS can lead to a challenging and rewarding career that also positively impacts & transforms patients’ lives. A SAS programmer with the Clinical knowledge always have an competitive edge over a purely SAS programmer as he/she will be in a position to take decisions while programming. One can start a career in Clinical SAS Programming as clinical programmer whose primary responsibility is writing programs in SAS to generate the output (tables, listings, and figures) needed for the analysis and reporting of the clinical study. A Clinical SAS Programmer having CDISC (standard specifications for electronically submitted clinical data)expertise would have extensive opportunities.

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Course Curriculum

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

Performing Common Analyses and Obtaining Statistics

  • Using the SAS XPORT Transport Format
  • Creating XML Files
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