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Showing posts from April, 2009

Helpful Hints on Developing a User Friendly Database

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Developing an effective database application requires an interface that is easy for the user. This paper will explore the features of SAS /AF and methodologies of building a successful database. It combines user interface suggestions for the front end while also suggesting back end SCL , SQL and data step logic that makes the software efficient to program and to operate. The majority of the examples are technical tips but there are also shared lessons learned from collaborating with end users which prove to be very important in creating an effective application. Overview There are many solutions for creating a data entry system ranging from a simple Excel spreadsheet to a sophisticated Oracle database. Each set of technologies works well for a specified task. This paper will explore a database containing clinical information used in regulatory submission. SAS /AF is very suitable for this since all analysis work for clinical data requires SAS . The scenario of this particular proj

How to Develop User Friendly Macros

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SAS ® macros help automate tasks that are done repeatedly. However, if they are not easy to use or debug, they may never be used. This paper will describe approaches to developing and maintaining SAS macros that are easy to use. Some of the topics covered include: effective documentation of macro header portable code for use with different OS error and warning message handling paper and online documentation use of nested macros and nested macro variables keeping macros simple for debugging A little effort can go a long way towards creating a successful SAS macro . This paper will present tips and techniques that are not always obvious. Besides getting the resulting numbers to the user, a user friendly macro can enhance the entire experience. Macros Overview SAS macros are great at automating repetitive tasks as a code generator. However, there are some features of macros that make them difficult to understand and debug. The syntax of SAS macros is similar to that of traditional

Making Code Review Painless

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Code review is an essential step in the development of concise and accurate SAS ® programs. It is a required verification step in performing validation in a regulated environment. This paper will present techniques and a macro that can be freely downloaded to automate this task. The % coderev macro will perform many of the common tasks during a code review including: 1. Spell checking headers and comments 2. Reviewing all input and output datasets of the program 3. Comparing defined macro variables versus macro variable usage 4. Checking for multiple macro calls that are not in a macro library 5. Evaluating hard code logic Evaluating sort order of all datasets These tasks are normally performed by an independent reviewer instead of the original programmer. By automating the tasks, the code review process will ensure that the smallest mistake can be captured through reports to ensure the highest quality and integrity. What normally is a dreaded task can now be done with ease. Code R

Outsouring and Offshoring SAS Programming

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Globalization is the reality of doing business in today's economic environment. SAS programmers and organizations that use SAS who choose to ignore it will face extinction. Outsourcing has had a significant effect on many industries dealing with information technologies. Knowledge workers face the same challenges now as manufacturing workers faced in previous decades. This paper will give you insights into offshore outsourcing as it pertains to SAS and provide strategies on how to navigate and work within this environment. Some of the topics discussed include: Pros and Cons of outsourcing SAS related programming Types of SAS programming within the Pharmaceutical industry that will be outsourced Strategies on successfully managing a local team while outsourcing SAS projects Outsourcing is not a new phenomenon but rather another step in the evolution of doing business in a technology driven global economy. SAS work is increasingly being outsourced to local Contract Research Or

Cost Effective Ways to Generate DEFINE.XML

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You can have greater understanding and management of your data if it is well documented with data definition documentation in the format of DEFINE. PDF and DEFINE.XML . As the number of datasets and variables increase, this can be very resource intensive. The time consuming documentation task is compounded by the fact that there are constant changes to the data so the documentation has to keep up with the changes in order for it to be useful and accurate. This paper will suggest methods and tools that would enable you to document your data definition document without purchasing a complex expensive system. Introduction When you plan for a road trip, you need a map. This is analogous to understanding the data that is going to be part of an electronic submission . The reviewer requires a road map in order to understand what all the variables are and how they are derived. It is within the interest of all team members involved to have the most accurate and concise documentation pertaini

Optimizing Your SAS Performance

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Google has become very successful by developing an efficient search engine running on commodity hardware. It no longer uses the old model of putting all its resource onto one super computer, but rather it spreads that processing onto a cluster of smaller machines running in parallel to form a grid . Gordon Moore made an observation in 1965 predicting that the number of transistors per square inch used on computers would double every year. This trend has become law and continues to elevate the ubiquitous and relatively inexpensive desktop and laptop computers. This paper will discuss how you can cluster computers in a grid to optimize the execution of SAS programs. Some of the techniques discussed include: Implementing supercomputer power with commodity hardware Submitting SAS programs sequentially while maintaining inter program dependencies Threading multiple groups of programs for optimal performance Measuring SAS performance with Statmark ™ , a standard metric for a cross plat

SAS for Excel Jockeys

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The ubiquity of Microsoft Excel and Word on desktop computers has made it a default entry point for many users to view and edit their information. Once Excel was included into the MS Office suite in 1993, it became the killer app overtaking other spreadsheet heavy weights such as Lotus 1-2-3. Although Excel has analysis capabilities, it does not have the powerful statistical procedures and depth of SAS . When analyzing certain types of data, such as financial information, Excel is the tool of choice. Its capabilities to easily generate graphs along with the visual pivot table provide powerful methods to view and analyze data . In certain cases, however, Excel is not capable of performing particular tasks which SAS can provide. Some of the topics that this paper will elaborate on include: Connecting SAS to Excel – The use of TCP port communication allows Excel to connect directly with a SAS session SAS Macro Management – Managing SAS macros that can be delivered to Excel

MedDRA and WHO Drug Easy as a Google Search?

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In a world where information can easily be accessed by applying a Google search, mapping unstructured clinicians term or verbatim terms from an adverse event or a drug name to a standard term no longer needs to be an arduous task. One of the challenges of working with coding medical terminology is combining several skills that are diverse from many different disciplines. The user needs to be clinically trained to understand and interpret the meaning of the adverse events or the drug names. A conceptual understanding of the normalized database and the multi-axial hierarchical structure is required to navigate the dictionary. The user must also be adept at adding to the source data and joining the case report form data with the proper fields of the dictionary tables to derive at the final mapped data. Expecting users to overcome these hurdles without a clear process or tools can lead to an error prone, laborious and painful process. This paper will address many of the issues confron

CDISC Implementation for Dummies

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CDISC (Clinical Data Interchange Standards Consortium) standards have been in development for many years. There have been major structural changes to the recommended standards from version 2 to 3. It is still an evolving process but it has reached a point of critical mass such that organizations are recognizing the benefits of taking the proposed standard data model out of the theoretical realm and putting it into real life applications. The complexity of clinical data coupled with technologies involved can make implementation of a new standard challenging. This paper will explore the pitfalls of the CDISC SDTM ( Submission Data Tabulation Model ) transformation and present methodologies and technologies that make the transformation of nonstandard data into CDISC efficient and accurate. There are some tasks within the process that can be applied asynchronously, but the majority of the steps depend on each other and therefore follow a sequence. The process is described below: It

Can Validating SAS Programs be Fun and Easy?

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Validation is normally a laborious and arduous task. This paper will present new methodologies and tools developed in SAS that will make the process painless. The goal is to add little or no effort from the user's perspective, yet gain the benefit of having a secured audit trail of all SAS programs during the development and verification process. Some benefits are described below: comparing differences between different versions of programs adding notes describing edit changes to each version adding a validation checklist of tasks associated during verification and validation managing status of development to production by applying version numbers such as version 1.2 generating reports for documentation and communication during validation After you realize the ease of use and the amount of quality control that can be gained, the task of validation becomes transparent and fun. Introduction Validating SAS programs presents some unique challenges especially when working within a r

Cloud Computing with SAS

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Cloud Computing is not a new computer architecture construct but there are several forces that are going to make it an alternative, if not the main way SAS software will be delivered in the future. This paper will detail some of the forces that are pushing many software solutions into Cloud Computing while describing how SAS is a microcosm of this transformation . Some of the topics being presented in this paper include: Cloud Computing Introduction Driving Forces for Change Software Components of Cloud Computing Requirements for Success The development of Cloud Computing has been in the making for some time. There are still some challenges and SAS needs to prepare and make a shift to this computing environment if it is to remain a dominant force in business intelligence software. CLOUD COMPUTING INTRODUCTION As software becomes more sophisticated to handle larger and more complex sets of data, the computer systems that run these applications also become more challenging to manage.

SAS Programmers Need to Know Regulations?

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Validation was introduced to the FDA in the mid 1970s but it is very much alive and relevant in today’s drug development environment. The recent recall of Merck’s Vioxx in September of 2004 after a study linked it to increase heart attack and stroke demonstrates the importance as to to why we need careful scrutiny from our regulatory review of the drug approval process in order to prevent such disasters. The need for validation is affirmed in the more recent event in July 2007 when the FDA concluded that GlaxoSmithKline ’s type 2 diabetes drug Avandia increases heart attack risk. Ideally, the FDA would be proactive in deciding on regulations that would prevent dangerous drug recall after many deaths due to drugs that has been proven to be harmful. However, historically, the FDA has been reactive in proposing precautionary procedures such as validation . The early proposals for validation were in direct response to problems with sterility as it involves the production of parent