This whitepaper outlines how the collaboration of organizations across science-based industries and their leveraging of advanced technology will improve lab processes and productivity. Digitalization will accelerate scientific creativity, bringing better products to market faster. Together these trends will not just benefit science but enable better care for patients as well.
White Papers
08 March 2018
With the rapid adoption of cloud computing, learn how Thermo Scientific™ Chromeleon™ CDS supports moving from a traditional on-premise setup to a cloud based deployment and associated benefits and challenges.
12 February 2018
21 CFR Part 11 requires Food and Drug Administration (FDA)-regulated industries, including medical device manufacturers, drug makers, biotech companies and biologics developers, to have validation documentation and implement controls such as audit trails and electronic signatures
31 January 2018
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
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.
Pages
Latest issue
Robert Roe interviews MathWorks Loren Dean, on the use of AI in modelling and simulation
Every device needs to work seamlessly in its operating environment. But when that environment is a human body, things get complicated.
Christian Marcazzo, general manager at IDBS, highlights trends in life sciences research and development.
Data is a company’s biggest asset, yet for any organisation, keeping a handle on the potentially vast volumes and diversity of data that are generated can represent a considerable issue.
Rob Lalonde, Univa’s cloud VP general manager, considers the unique challenges posed by HPC
Deep learning has seen a huge rise in popularity over the last five years in both enterprise and scientific applications.
HPC users are increasingly turning to cloud technologies due to their flexibility and scalability, allowing them to quickly change the size of their workloads, adopt new technologies in a small testing environment and to help to increase the agility of a company working across multiple sites, or
