Automation

Manual No More: Automating the Scientific Data Lifecycle

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Some 50-80% of research scientists' and data scientists' time is spent wrestling with data before they can focus on higher value AI/ML and advanced analysis to help bring new life-saving therapeutics to market. This paper describes how a complete reimagining of discovery and development to drive scientific outcomes leads to a new world where science is accelerated with FAIR (Findable, Accessible, Interoperable, Reusable) harmonized data in the cloud.

Considerations for the digital laboratory

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Credit: Gorodenkoff/Shutterstock

Automation, robotics and digital technologies are transforming laboratory processes in life sciences, R&D and manufacturing, and driving a new era in data-focused disease and drug discovery. While the lab sector is still on an evolutionary road to the fully automated lab-of-the-future, or Laboratory 4.0, digital transformation is accelerating the move away from analog processes, and so reducing the need for paper-based and manual processes and human intervention.

Open automation

Sophia Ktori discusses the importance of integration and open systems in supporting laboratory automation

Reducing Risk & Improving Synthesis Outcomes with SYNTHIA Retrosynthesis Software

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Addressing the many intrinsic and external challenges to chemical synthesis has led to a highly complex system of regulations that involve numerous academic and governmental organizations in modern times. Existing methods have now been bolstered by powerful computer software with advanced algorithms to support the synthetic chemist and this is leading to new and innovative drugs that can be developed faster and with less risk.

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