SAS Clinical Training

TABLE OF CONTENTS

1. Introduction to Clinical Trials

   Overview of highly regulated drug development process, from discovery to bringing a biopharmaceutical product to market

   • Pharmaceutical Industry vocabulary
   • Programmer work description
   • The Drug/Device Development Process
   • Overview of Good clinical practice (GCP)
   • What is a clinical trial? What are the different types of clinical trials?
   • Why participate in a clinical trial?
   • Where do the ideas for trials come from?
   • Who sponsors clinical trials?
   • What is a protocol?
   • What is informed consent?
   • What is a placebo?
   • What is a control or control group?
   • What are the phases of clinical trials? Understanding major phases (Phase I– IV) and clinical data management.
   • Learning rationale for each phases of drug development cycle and introducing role of SAS programmer in each phase.
   • Different types of reports generated by programmer in clinical trials.
   • Food and Drug Administration (FDA) regulations and Guidance (21 CFR part 11, GCP, eCTD)
   • Regulatory overview and approval process including IND/NDA to FDA
2. 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
   • Working with real pharmaceutical industry data (demographics, concomitant medication, medical history, laboratory data, adverse event, end point data, etc.)
3. Using SAS to Create Analysis Data sets
   • Learning tips and tricks to create and manage 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
4. Generate Customized Clinical Trials Tables, Listings and Graphs/Figures
   • Creating Tables and Listings
   • 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
   • Creating Kaplan-Meier Plot using PROC GPLOT or PROC LIFETEST
5. Clinical Trials Process
   • Interpret a Statistical Analysis Plan (SAP).
   • Derive programming requirements from an SAP and an annotated Case Report Form (CRF).
   • Describe regulatory requirements - Principles of 21 CFR Part 11, International Conference on Harmonization, Good Clinical Practices.
   • Clinical Trials Data Structures
   • Identify the classes of clinical trials data - Demographic, Lab, Baseline, Concomitant Medication, etc.
   • Identify key CDISC principals and terms.
   • Describe the structure and purpose of the CDISC SDTM data model.
   • Describe the structure and purpose of the CDISC ADAM data model.
   • Describe the contents and purpose of define.xml.
   • Import and Export Clinical Trials Data
   • Efficiently import and subset SAS data sets.
   • Examine and explore clinical trials input data - Find outliers, missing vs. zero values, etc.
   • Apply categorization and windowing techniques to clinical trials data.
   • Apply ‘observations carry forward techniques’ to clinical trials data (LOCF,BOCF, WOCF).
   • Calculate ‘change from baseline’ results.
   • Obtain counts of events in clinical trials.Use SAS procedures to obtain descriptive statistics for clinical trials data -FREQ, UNIVARIATE, MEANS, SUMMARY
   • Use PROC FREQ to obtain p-values for categorical data (2×2 and NxP test for association).
   • Use PROC TTEST to obtain p-values for continuous data (one-sample,paired and two-sample t-tests).
   • Identify and describe SAS procedures used to perform ANOVA.
   • Macro Programming for Clinical Trials
   • Report Clinical Trials Results
   • Validate Clinical Trial Data Reporting
   • Explain the principles of programming validation in the clinical trial industry.
   • Utilize the log file to validate clinical trial data reporting.
   • Use programming techniques to validate clinical trial data reporting (PROCCOMPARE, MSGLEVEL).

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