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By Kevin Moore
When looking to maximize productivity in life science R&D, drug discovery, clinical studies or clinical diagnostics, laboratory automation is a crucial element. You may already have identified great solutions to automate individual applications and steps in your workflows, but unless these systems work together harmoniously, your lab’s overall productivity could still fall short of the mark. Whether your application area involves clinical diagnostics, genomics, cell biology, drug discovery, protein purification or something else altogether, we’ve identified some of the most common roadblocks to successful automation.
By Kevin Moore
Always a great forum for networking and sharing information on the latest developments and trends in laboratory automation, SLAS didn’t disappoint this year. The biggest buzz in 2018 focused on the increasingly important role that genomics is playing in the discovery of therapeutic proteins and the ability to target those drugs to specific gene mutations.
By Claudio Bui
When introducing a new product to the automated liquid handling market, getting there first with high quality and reliable hardware is vital to capturing and maintaining early market leadership. How can you gain that advantage when you have to balance requirements for customized high-performance robotics against an accelerated product launch?
By Jason Meredith
No matter how much you invest in a liquid handling automation system, it’s next to worthless without well-designed software. The hardware and robotics are certainly critical, but it is the software that can make a big difference in how easily you can program your system, tailor it to meet your needs, and track samples securely.
By Siegfried Sasshofer
An automated liquid handler for sample processing can significantly increase your productivity. It becomes even more powerful when integrated with other workflow components to enable you to create fully automated walkaway processing for applications such as sample and library prep for next generation sequencing (NGS), or cell-based assays. The question is how to choose components and integrate them.