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Accelrys’ Experiment Knowledge Base (EKB) is a laboratory informatics system that raises the bar for experimentation management and enables organizations to transform mass amounts of scientific data into knowledge essential for faster, more efficient new product innovation. Accelrys’ Experiment Knowledge Base (EKB) is a laboratory informatics system that raises the bar for experimentation management and enables organizations to transform mass amounts of scientific data into knowledge essential for faster, more efficient new product innovation. Designed specifically for R&D, the system offers scientists, for the first time, the ability to search and mine experimentation data from almost any source. It also provides integration and interoperability with existing lab equipment and applications as well as features for improving experimentation management and collaboration. With a flexible, modular and integrated approach to data search and experimentation management, the system overcomes the failures of poorly architected legacy R&D informatics systems that have not kept pace with today’s fast-changing business environments and the large amounts of complex data generated. This informatics system offers scientists a single system for efficient searching, analysis and mining of data from virtually any source based on capability to Extract, Transform and Load (ETL). Additionally, the “data mart” approach allows end users to consider new ways to query data every day, without the necessity to re-architect the system or its database. The system is applicable to many industries and areas of science and has been successfully deployed for catalyst design, petrochemical processing, biofermentation, formulations design and more. It leverages four key capabilities in a modular architecture to increase innovation velocity and consistency by reducing or eliminating repeat experiments, enhancing laboratory efficiency, improving experimentation consistency and extracting knowledge from data. Capabilities include: planning and design of experiments and campaigns; step-by-step execution of experiments; capture of experiments and sample data; and search and analysis of experiments and sample data by properties/descriptors. By leveraging the company’s Enterprise Platform, the system also complements document-centric systems such as ELNs and downstream systems focused on scale-up, manufacturing and compliance to support an end-to-end, integrated scientific innovation lifecycle management approach. Integration with ELNs also streamlines project documentation while improving global collaboration and intellectual property protection.

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