Journal
COMBINATORIAL CHEMISTRY & HIGH THROUGHPUT SCREENING
Volume 14, Issue 10, Pages 861-871Publisher
BENTHAM SCIENCE PUBL LTD
DOI: 10.2174/138620711797537085
Keywords
Cloud architecture; cloud computing; discovery-cloud; docking; grid computing; high content screening; high throughput screening; microarrays; next-generation sequencing; on-demand computing
Funding
- MGL
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Continued advancements in the area of technology have helped high throughput screening (HTS) evolve from a linear to parallel approach by performing system level screening. Advanced experimental methods used for HTS at various steps of drug discovery (i.e. target identification, target validation, lead identification and lead validation) can generate data of the order of terabytes. As a consequence, there is pressing need to store, manage, mine and analyze this data to identify informational tags. This need is again posing challenges to computer scientists to offer the matching hardware and software infrastructure, while managing the varying degree of desired computational power. Therefore, the potential of On-Demand Hardware and Software as a Service (SAAS) delivery mechanisms cannot be denied. This on-demand computing, largely referred to as Cloud Computing, is now transforming the drug discovery research. Also, integration of Cloud computing with parallel computing is certainly expanding its footprint in the life sciences community. The speed, efficiency and cost effectiveness have made cloud computing a 'good to have tool' for researchers, providing them significant flexibility, allowing them to focus on the 'what' of science and not the 'how'. Once reached to its maturity, Discovery-Cloud would fit best to manage drug discovery and clinical development data, generated using advanced HTS techniques, hence supporting the vision of personalized medicine.
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