SAS - Statistical Analysis System
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. In addition to doctors and clinicians who collect clinical trial data, the group conducting data analysis includes statisticians, clinical data managers (COMs) and SAS programmers. Statisticians provide the ideas and methods of the data analysis, clinical data managers manage the collected data and control the data quality. In between, SAS programmers implement the analysis methods on the collected data and provide the study summary tables, data listing and graphs to the statisticians andlor clinicians to write study report. SAS programmers work closely with statisticians and data managers. They provide the link between raw data and the analysis. This paper discusses the SAS programmers' roles in the clinical trial data analysis task flow, describes the SAS programmers' tasks and skills, and provides insight on how to work with people in the team.
Validation is a critical component to programming clinical trial analysis. Essential to effective validation is the programmer's understanding of the data with which they'll be working. If you don't understand how the data is arranged, the values that are reasonable for each variable, and the way the data should behave, you cannot ensure that the final result of your programming effort is complete or even appropriate. Therefore, to be a successful programmer in the pharmaceutical industry, you need to understand validation requirements and to learn how to make the code do the bulk of the work so that your programs are efficient as well as accurate. This indispensable guide focuses on validating programs written to support the clinical trial process from after the data collection stage to generating reports and submitting data and in your output topics addressed include:
- Validation and pharmaceutical industry overviews
- Documentation and maintenance requirements discussions
- General techniques to facilitate validation
- Data importing and exporting
- Common data types
- Reporting and statistics
Validating Clinical Trial Data Reporting with SAS is designed for SAS programmers who are new to the pharmaceutical industry as well as for those seeking a good foundation for validation in the SAS programming arena. Readers should have a working knowledge of Base SAS and a basic understanding of programming tasks in the pharmaceutical industry.
In Information and Technology area, managing huge databases and analyzing the data is a challenging task. For managing data, warehouses are created as per the client’s specifications and requirements and variety of software tools are used to process the data.
Statistical Analysis System, known as SAS System, is one of the most widely used, flexible data processing tools. It is used to perform:
- Data entry, retrieval and management
- Report writing and graphics
- Statistical and mathematical analysis
- Business forecasting and decision support
- Operations research and project management
- Application development
The core of the SAS System is base SAS software. It consists of
SAS language: It is a programming language that you use to manage data
Procedure that are software tools for data analysis and reporting
A macro facility, A windowing environment called the SAS Display Manager System.
SAS Software Overview
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 advanced options through the SAS programming language. SAS programs have a DATA step, which retrieves and manipulates data, usually creating a SAS data set, and a PROC step, which analyzes the data.
Each step consists of a series of statements.The DATA step has executable statements that result in the software taking an action, and declarative statements that provide instructions to read a data set or alter the data's appearance.The DATA step has two phases, compilation and execution. In the compilation phase, declarative statements are processed and syntax errors are identified. Afterwards, the execution phase processes each executable statement sequentially.Data sets are organized into tables with rows called "observations" and columns called "variables". Additionally, each piece of data has a descriptor and a value.
The PROC step consists of PROC statements that call upon named procedures. Procedures perform analysis and reporting on data sets to produce statistics, analyses and graphics. There are more than 300 procedures and each one contains a substantial body of programming and statistical work.PROC statements can also display results, sort data or perform other operations. SAS Macros are pieces of code or variables that are coded once and referenced to perform repetitive tasks.
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 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
Before analyze the data and produce the final report we have to arrange the data in the order (format) that the software will recognize the data for further processing. SAS will recognize the data in the form of data set. SAS data set consists of two parts i.e.Descriptor information: This describes the contents of the SAS data set to the SAS System. Data values: Data that have been collected or calculated which is organized into a rectangular structure containing rows called observations and columns called variables.
Syntax of SAS language
SAS language consists of statements. Each SAS statement is terminated by semi-colon (;) When SAS program is executed, log and lst (list or output) files are created by the system.
Log file contains the Error messages, Warnings and Notes. Whenever we run the SAS program, the first step is to open the log file and check for the errors, warnings and notes. This will help us the make the SAS program error free. When the log file is no errors, no warnings, no notes (it displays at the bottom of the log file specifying Warnings 0 Errors 0 Notes 0) then we can confirm that the processing is accurate.
Output file It contains the results of the processing. Base SAS mainly completes with two steps called Data Step and Procedure Step.
Data Step It is used to create data sets. Proc Step is used to execute the pre-defined procedures that are used for processing.
Running the System
We can start SAS session with the SAS command. SAS system can be used in different environments like DOS, Windows, NT, Unix, MVS, VMS etc.
SAS programs can be run in the following methods:
- Display Manager Mode: This method is used in windowing environment. We can edit and execute programming statement, display the SAS log and output windows.
- Interactive Line Mode: In this mode, program statements are entered in sequence in response to prompts from the SAS system.
- Non-interactive mode: SAS program statements are stored in an external file and executes immediately.
- Batch mode: we can run SAS jobs in batch mode under host systems batch or background executive.
Data Step and processing
This is the main part to create a data or to describe the data that SAS system recognizes for processing. A Data step is a group of SAS language statements that begins with DATA statement and followed by programming statements that perform the manipulations necessary to build the data sets. Report writing, file management and information retrieval can all handled in the Data Step. We can submit the Data step to the SAS system for execution. SAS System first compiles and then execute.
- SAS system checks the syntax of the SAS statements and compiles them, while compile, it translates the statements into machine code.
- DATA statement dataset name (begins step)
- Input or Set, Merge or Update (reads a record from input data)
- Optional SAS programming statements (further process the data)
- Run (end of the data step)
- Sample DATA Step: Data weight; Input rollno sub1 sub2 sub3 ; Total=sum(sub1,sub2,sub3); Datalines; 1001 90 80 75 1003 80 85 87 1004 90 95 90
Industries Adopted SAS
- Financial Services
- Government & Education
- Life Sciences
- Media & Entertainment
SAS in Pharmaceutical
- FDA's most preferred tool for Clinical trials for Phase I, II, III, IV etc. Only validated tool,which create regular opportunities for SAS, trained consultants.
- All major pharmaceutical companies USE SAS as the analysis tool for clinical research.
- On an average, a drug takes 12 –13 years to reach the market, therefore utilizations of SAS in all phase creates great opportunities for SAS trained consultants.
- On an average 6000-8000 clinical trials are conducted every year. Great Demand for SAS trained Consultants.
- Always there is a demand for the SAS consultants all through the year and years to come
Each training session will be based on the topic and discussion.
- Introduction to Healthcare Industry
- Introduction to Pharmaceutical Industry
- Concepts of Pharmacokinetic / Pharmacodynamic
- Design and development of CRF-Case Report Forms
- Fundamentals of Statistics related to SAS Tools and Technology
- Introduction to SAS Analysis tool and its applications
- Organizational Structure of Clinical Research Development
- Creating Analysis Datasets and Workshop
- SAS Functions and Workshop
- SAS Statements and Workshop
- SAS Procedure and Workshop
- SAS SQL and Workshop
- SAS Macros and Workshop
- SAS Import, Export and Workshop
- Analytical technique of SAS Graphs and Workshop
- Mock Interview Practice – optional