Different Paths to Clinical SAS Programming

I interviewed several friends to learn how they became a SAS programmer in the Pharmaceutical industry and found that their background varied greatly. There were some common themes however which are gems of information. These ideas resonates with me upon reflections with my own career decisions. There are many lessons that can be learn which when I just listen to their stories, they reveal themselves. I'll share one of these stories here.

Introduction
There are many paths that individuals take to arrive at a career as a SAS Programmer. SAS is a programming language which requires the rigors of a computer scientist. However, to become a clinical trials analyst also requires a thorough understanding and knowledge of the clinical data to be analyzed. The combination of these distinct skills attracts people from diverse backgrounds. It is surprising to find so many different backgrounds of individuals with differing talents and interests who gravitate towards this career path. Like many other career paths dealing with technology, things change. The dynamic aspects of the job require programmers to become resourceful in order to survive. They therefore must re-invent themselves continuously. The core understanding of the analytics behind clinical trials is still evolving but remains comparatively stable. Once you gain a thorough understanding of clinical data and the accompanying programming techniques, you then have a good foundation for becoming a successful Clinical Trials Programmer.

There is no one correct path but rather an abundance and diverse set. The diversity of people who succeed in this field illustrates the fact that it requires a unique combination of skill sets needed to thrive in this environment. This career path has only recently been established so many of the individuals who entered this field did not initially set out to become a clinical SAS programmer. For many, the journey was unplanned and there were no road maps. They are pioneers and navigated their career paths following their intuition and relied on luck. There are many lessons that can be gained from these pioneers. The paths which these individuals paved will provide a clearer vision and set of directions for future aspiring SAS programmers who plan to venture on the same road.

Consulting SAS Programmer – Gene
There were corporate challenges at VISX which lead to layoffs. This and other management turmoil lead Gene to try out the consulting world starting with work at Roche Biosciences. He started out with a three month contract which is typical for an initial contract. This introductory period allowed the company to evaluate the consultant to see if it worked out without making a big commitment. If things went smoothly and there was work to be done, the contract normally got extended. Gene worked on the precursor to Oracle Clinical known as Rx/Clinical which is the clinical trials relational database jointly developed by Oracle and Syntex. Syntex also later became Roche Biosciences. Even though he started out working in the role as a data manager, Gene grew into the position of a SAS programmer and continued to work as a consultant at Roche for three and a half years. This was where he learned the majority of his SAS programming skills. During these same years, Gene noticed that there were some individuals in this large organization who began to have a “DMV” mentality. After years of working in a large bureaucratic organization, they lacked the desire to learn new things and became less motivated. Some of his colleagues were in the same company for tens of years. He began to see how this stagnation crept into his work routine as well, even though he was a consultant. This realization woke Gene up to the reality that perhaps he was also falling into this stagnation. In attempts to being true to his original motivation for becoming a consultant, he decided to make a change.

Gene ventured into a short contract with Quintiles Pacific down the Peninsula in Mountain View. This was the first time he worked within a Clinical Research Organization (CRO) which was different from his experience with a pharmaceutical company. His initial thoughts were that since it was a service organization, the work would be varied since they were servicing many different clients at the same time. It turned out however that many clients rely on the CRO to dictate the standards. It therefore turned out that the work was still done mostly in the same way across different clients and projects.

The desire to learn new things and to work in different environments drove Gene to search for new projects. He had heard from other SAS consultants that finding jobs on your own was the way to earn the biggest salary. Despite this fact, Gene relied on job placement firms such as Trilogy and ASG to land him new opportunities. Gene preferred working in this manner because he preferred to take advantage of the marketing resources of these firms to find him the projects so he could focus on “doing the work and not trying to find the work”. With a little luck, there is always something new and interesting to learn within each work environment. At Pharmacyclics, he worked with the Trialex System which was a browser based thin client software to manage reports and analysis files he created using SAS. It was a dynamic time with new tools and methodologies to keep him on his toes.

Now living in North Carolina, he works for Schwarz Bioscience which is based in Germany. In this position, Gene works at home most of the time connecting to servers in Germany. When Gene started, they did not have cube space in their North Carolina office, so the arrangement was for him to connect via his cable modem from home and work through a remote desktop using Citrix remote desktop technologies. Most of the time, it worked well but once in a while, his keyboard would spontaneously switch to a German style keyboard and his Ultraedit editor would create unexpected characters so he would have to log out and back in to regain the use of an English keyboard.

Different organizations have different approaches towards validation of SAS programs. This is partly due to varying interpretations of the regulations and also due to how different managers and organizations function. At this current project, Schwarz Biosciences has an approach of validating all the output 100%. This means that there is an independent programmer who would re-produce the same numbers in a separate SAS program stored in a separate SAS dataset which is distinct from those that are meant to be submitted to the FDA. The new dataset would then be compared to the submitted data through the use of PROC COMPARE to ensure that the two sets of numbers are identical before it is deemed “validated”. When Gene first started, he primarily did the duplicate validation type programming. Now that he has been on the project longer, he is appointed to perform more of the original programming that will be part of the submission.

Since he works remotely, Gene’s main method of communicating with his coworkers is through email. Ninety percent of the time, his email and communications are dealing with detailed information such as data, file, and variable names. He does recognize that at times, it does take a little longer to describe or show someone something in an email compared to just being physically in front of them. Even with these challenges, Gene has adapted and rather prefers this arrangement and feels perhaps that this is the direction in which SAS programming is going to move towards in the future.

more to come in the book I am working on "Becoming a SAS Programmer in Pharmaceutical and Biotech Industry"...