Get the latest insights, innovation and commentary from Automata experts and external contributors in our lab automation blogs. Discover the impact of lab automation across different workflows and industries, from scaling up ELISA development in drug discovery processes to supercharging CRO labs.
Discover how life sciences face challenges in managing vast, complex data and how automation can enhance data quality, accessibility, compliance, and efficiency, driving innovation and faster discoveries.
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Explore the top five challenges in lab automation and get some practical solutions to overcome them.
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Cloud-first lab automation provides superior benefits to modern labs vs on-site solutions. Find out why in this new article from Automata
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Nick Lench, Genomics Expert and Co-Founder of Congenica, discusses the challenges holding back genomics and how automation will usher in a new era of...
Following the NHS' collaboration with automation leader, Automata, to accelerate lab automation, Peter Baker, commercial director at University Hospital Southampton NHS Foundation Trust (UHS),...
Find out what some of the biggest themes and challenges are within the alternative protein industry and how innovative technology can help.
Automating mammalian cell culture can improve the scale and quality of results for labs. We look at how labs can implement easy automation wins...
As cell cultures become more advanced, optimising culture quality is more important than ever Cell culture is an essential in vitro research tool that...
We sit down with Marko Storch, Head of Synthetic Biology and Automation, London Biofoundry, to talk about tackling the challenges of lab-grown meat
As demand for cell culture increases, labs are under pressure to scale - and reducing manual processes is critical
Genomic sequencing will revolutionise healthcare over the next decade. We take a look at the changes it will bring to today’s challenges.
We look at what causes errors in biology lab experiments and how lab automation can help reduce them
Manual colony counting is repetitive and error-prone, but, with automation, it can be done faster and more accurately
