Cloud Computing in Life Sciences R&D
Author: Ken Rubenstein, PhD
The pharmaceutical outsourcing trend and economic restrictions, coupled with the increasing attractiveness of cloud computing offerings, have created a highly dynamic yet nascent market. Included in this report:
Technological aspects of cloud computing and activities of companies that are active in the field
Current and emerging applications of cloud computing, with special emphasis on next-generation sequencing and its resultant data
Market aspects of cloud computing, including competition among providers and user requirements
Results and analysis from an extensive survey of bioinformatics people concerning their practices and views
General observations, conclusions, and possible future trends
Cloud computing is rapidly growing in importance as life science R&D organizations are deluged with data from multiple sources. Simultaneously, demand for computationally complex modeling and simulation studies continues to rise dramatically. Limited funding and budgets make it difficult for many organizations to build the infrastructure necessary to keep pace with these challenges. Cloud computing appears for many as a promising alternative to in-house expansion. The intersection of the outsourcing trend and economic restrictions with the increasing attractiveness of cloud computing offerings has created a highly dynamic, yet nascent, market.
Cloud Computing in Life Sciences R&D analyzes this environment and market, and offers suggestions as to where they might be heading. Following a brief introductory chapter, the second chapter covers the evolution of cloud computing and explores the underlying concepts that provide context for deeper understanding of the subject. Chapter 3 examines the technological aspects of cloud computing and introduces the companies, both large and small, that are active in the field.
Chapter 4 turns to applications of cloud computing, with special emphasis on next-generation sequencing and its ever-increasing burden of data that needs to be processed and interpreted. Other application areas that appear particularly suitable for cloud computing include protein docking, modeling and simulation, and data mining. Given bullish signals for the future of cloud computing in life sciences, we expect the number and diversity of applications to increase markedly over the next five years.
The fifth chapter views cloud computing from the market perspective, examining competition among providers and user requirements. For this report, we divide the cloud services user market into three segments: large pharmaceutical and biotechnology companies; small to medium-sized pharmaceutical and biotechnology companies; and academic and institutional non-profit organizations. Certainly, organizations in all three of these categories face budgetary challenges in these troubled and uncertain times. Consequently, the cloud computing business model has great appeal across the board.
Cloud computing is still in its early days, and most life science organizations are still proceeding cautiously to test its feasibility and determine which applications run best in that mode. Yet driven by continual acceleration in the rates of data generation and the desire for processor-intensive applications, these organizations continue to increase their cloud utilization and the diversity of applications they run there.
ABOUT THE AUTHOR
Ken Rubenstein, PhD, a biochemist and molecular biologist, received his PhD at the University of Wisconsin and postdoctoral training at the University of Pennsylvania School of Medicine. He was a key innovator and research manager for Syva Company, the diagnostics branch of Syntex Corporation. During his 13 years with Syva, Dr. Rubenstein became vice president, scientific affairs, a function that included strategic planning. Since 1983, he has served as a technology and marketing consultant to biomedical companies and an industry analyst, with more than 40 published studies to his credit.