R&D-driven industries talk a lot about progressing towards the paperless laboratory. The ultimate aim is to capture and store all experimental, process, inventory and results data, from the earliest stages of discovery, through to manufacturing, QA/QC and even instrument management, in an electronic format
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31 January 2018
03 August 2017
Data governance is an integral part of a regulated company’s quality system. Having a chromatography data system can simplify system administration and ensure regulatory compliance (including 21 CFR Part 11) and adherence to data integrity guidelines.
08 June 2017
Audit trails are considered the key to the security of a system since they track changes to data and metadata. In this way, an incomplete or absent audit trail can impact data integrity or even product quality. The absence of an audit trail is considered to be, “highly significant when there are data discrepancies” according to the FDA.
08 June 2017
Today, laboratory-based organizations face a wide variety of unaddressed data management challenges, and yet ultimately the scientific data is the currency with which they trade. Proper data management may not pay shareholders but it fundamentally defines the integrity of the organization and it’s purpose for existing. Being the cheapest, the fastest or the most definitive is desirable but it is all meaningless if the data is untrustworthy.
08 June 2017
Externalization of R&D activities and the deluge of instrumental analytical data generated on a daily basis has resulted in increasing interest in analytical data standardization. Any standardization efforts, however, to either a single format or for data exchange between formats; should be weighed against the requirements of different users of that data, and hardware innovations.
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As not only the HPC industry but the larger computing ecosystem tries to overcome the slowdown and eventual end of transistor scaling described by Moore’s Law, scientists and researchers are implementing programmes that will define the technologies and new materials needed to supplement, or repla
Architectural specialisation is one option to continue to improve performance beyond the limits imposed by the slow down in Moore’s Law.
As the complexity of both HPC hardware and the challenges that scientists are trying to solve using HPC systems increases, ensuring a system is utilised efficiently is necessary to deliver a computing service with value for money and a high research output.
With data rates increasing and more complex challenges arising in life sciences, Panasas’ Jim Donovan and Dale Brantly discuss the benefits of using HPC for these workloads