Life Sciences

Labs of the Future - Enabling Integrated Research Labs with Cloud Technology

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Modernizing Clinical Trials: Digital Technologies and the Cloud 2 Published by FiercePharma S cientists in leading research labs across the world struggle to store, analyze, integrate, and share data sets simply. Data is created from a wide variety of equipment types and manufac turers, and in many cases, that data is only stored on local servers. The majority of these labs are not set up to optimize the researchers' workday or streamline repetitive and time-consuming processes. Yet, with innovative thinking and the help of technology- based solutions, some research environments are addressing and solving these problems, creating a fully integrated 'lab of the future' that is data-driven and optimizes researchers time spent on scientific experimentation. Establishing a digitized lab helps protect the valuable data researchers generate and can accelerate the research and discover y process by leveraging new technologies like machine learning. A lab of the future would enable automated data backup and archiving, fast data analysis, integration of artificial intelligence to reduce the amount of time researchers spend on tedious tasks, and secure collaborations with other researchers internally and externally. Industr y figures show that over a 10 -year period beginning in 20 05, over 9,0 0 0 new par tner ships were formed bet ween pharmaceutical companies, with the goal of collaborating to innovate new drugs more quickly. 1 Seamless integration with ex ternal par tners, while protecting organizational intellectual property (IP), will be vital to making these partnerships successful. Amazon Web Ser vices (AWS) is making integrated research labs a reality through automated data storage from legacy equipment, secure data sharing to facilitate collaboration, and implementation of standardized data formatting. With data securely in the cloud, AWS makes it simple to collaborate with global research teams, utilize on-demand high- per formance computing for analysis, and implement ar tificial intelligence or machine learning to speed time to ac tionable insights. 1 Reh, Greg, et al. "Collaboration as a key to success in pharmaceutical R&D." Health Care Current, Jan. 17, 2017, w w w2.deloit te.com/us/en/pages/life -sciences-and-health- care/ ar ticles/health- care - current-januar y17-2017.html.

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