To mark its 10th anniversary, Drug Discovery & Development magazine invited industry vendors to reflect on the history and made predictions about future of the industry. Featured here are verbatim comments from this company.

SAS

Headquarters 
Cary, N.C.

Years in Drug Research 
30 Years

Spokesperson
Jason Burke, Worldwide Director of Health and Life Sciences

Web site 

About the company
SAS is the leader in business intelligence and analytical software and services. As the de facto standard for clinical data analysis and the choice of 100% of the Fortune 500 life sciences companies, SAS assures accurate, comprehensive, and reliable analysis of life sciences research and business data with a portfolio of integrated solutions that drive efficiencies and deeper insights throughout every stage of a therapy’s lifecycle: from discovery, through development, commercialization and beyond.

The company’s line of business as it was 10 years ago. Changes in life science/drug research that influenced business.
SAS Institute got its start by building statistical tools for businesses, with pharmaceutical research being one of the earliest focus areas. Right at 10 years ago, the company made a strategic decision to expand its focus and begin building horizontal solutions that were more tailor-made to the needs of specific businesses. This evolution eventually resulted in the formation of modern industry solutions such as SAS Drug Development. Industry shifts from paper-based to electronic-based clinical data capture and management served to drive SAS towards stronger controls around regulatory compliance (e.g., 21CFR Part 11) in our solutions and more sophisticated analytics.

Scientific challenges in the next 10 years.
Our science is evolving from its historical roots in discrete research to a diverse network of scientifically-relevant information coming from many sources and structures. As institutions will be increasingly reliant on data from external researchers, real challenges with data pedigree and semantic interpretation of findings will arise. Drug candidates will be defined through chemical, biological, molecular, genetic, and systemic properties. But these properties will be explored through research programs that will be more dynamic and responsive to accumulated findings over longer time horizons. Rather than simply challenging the statistical validity of findings, this flexibility will produce real questions in how to appropriately identify and manage life-critical research design changes. The explosive growth in data volumes will reflect a growing inclusion of unstructured information, and increased focus will be placed in getting information directly from real-world patients as opposed to just clinical trial participants.

Factor(s) that drove the development of technologies during the last 10 years and greatest area of growths.
One of the largest forces impacting software development has been regulatory compliance driven from 21 CFR Part 11 which established both functional and quality requirements for these technologies. Beyond the evolving regulatory landscape, genetic, genomic, proteomic, and microarray technologies marshaled a diversification in the way companies think of their research assets and programs. The use of desktop visualization software, for example, unlocked new ways of rapidly gaining insight into research results. These forces, combined with the need for greater insights into the long-term safety profile of therapies, have resulted in two fundamental drivers: the increased need for diverse data aggregation, and the maturation of software from niche applications to enterprise-class software systems driven by standards. To that end, the progress of the Clinical Data Interchange Standards Consortium has been instrumental in lowering the boundaries within and between companies in terms of their ability to meaningfully share information.

Bold Prediction: Where will drug research technology be in 10 years?
The next 10 years will dwarf the past 10 years in its impact. The progressive adoption of patient- and institutionally-driven electronic medical records and medical devices will unlock new opportunities for studying disease prevalence, progression, and outcomes. Advancements in healthcare and pharmaceutical industry standards will enable new types of information sharing and analyses conducted in dramatically shorter time. And technology cost reductions associated with genetic analyses will bring personal genetic profiles and traits into the mainstream of medicine—first as a point of consumer interest, but then as a tool for assessing health risks and eventually drug outcomes.