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Deep Learning-Based Genedata Imagence® for Automated High-Content Image Analysis Debuts at SLAS Conference

Genedata, a leading provider of advanced software solutions for biopharmaceutical R&D, today announced Genedata Imagence®, the industry’s first commercial and instrument-agnostic software that automates the analysis of high-content screening (HCS) images. The deep learning-based solution accelerates, by orders of magnitude, the time-consuming and complex process of analyzing phenotypic high-content images. Delivering reproducible, unbiased results proven to be equal to or better than results from more traditional analysis approaches, the solution enables biologists to quickly and routinely set up and analyze high-content screens without requiring image analysis expertise. Genedata Imagence will be demonstrated at the SLAS Advanced 3D Human Models and High-Content Analysis Conference (Leiden, Netherlands; Oct. 17-19, 2018).

Game Changer: Genedata Imagence Reduces Analysis Time from Weeks to Hours
Genedata Imagence is the result of several collaborations between Genedata and leaders in the biopharmaceutical industry who had expressed the need for a more efficient HCS image analysis process. To address this need, Genedata invested significant resources in developing Genedata Imagence – the first commercial software solution that meets key requirements for this specific process. A joint project with AstraZeneca, based on Genedata Imagence technology, was awarded the 2018 Bio-IT World Best Practices Award for the innovation and value that the solution brings to the industry. This project demonstrated how the technology can automatically transfer learnings from one assay to another, allowing a very rapid set-up of analysis workflows for new assays. The deep learning-based solution was tested and proven with pharmacologically relevant parameters used on a very typical workflow for assay development. This collaboration also validated in real-life settings the quality of results generated by Genedata Imagence.

Deep learning has the potential to be a real game changer when applied to the analysis of phenotypic high-content screens. Genedata collaboration partners identify value in three key areas: the ability to increase the speed at which data are processed and reduce the time it takes to fine-tune assays; elimination of human bias; and most importantly, enabling scientists to better understand and examine specific cell biology.

Ultimately, Genedata Imagence will enable pharmaceutical R&D groups to broadly implement and automate the analysis of phenotypic high content screens and significantly scale-up their HCS operations, thereby reducing time consuming, labor intensive work while fueling faster delivery of R&D projects.

Interested parties can explore the technology through the Genedata Early Access program. The program allows customers early adoption of Genedata Imagence to their own projects and provides an opportunity to learn how the solution can improve existing workflows. The software is scheduled for licensing in early 2019.

“With Genedata Imagence, we provide a highly innovative solution for HCS image analysis that will revolutionize a key process in biopharmaceutical R&D,” said Dr. Othmar Pfannes, CEO of Genedata. “We are committed to using cutting-edge technologies such as AI and deep learning that drive improved efficiencies in biopharmaceutical R&D processes, and eager to advance further collaborations to this end with industry leaders.”

Editorial Note: To schedule a Genedata Imagence demonstration at the SLAS Advanced 3D Human Models and High-Content Analysis Conference, email

About Genedata
Genedata transforms data into intelligence with innovative software solutions and domain-specific consulting services that automate complex, large-scale experimental processes and enable organizations to maximize the ROI from their R&D. Founded in 1997, Genedata is headquartered in Switzerland and has offices in Germany, the UK, Japan, and the US.
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The statements in this press release that relate to future plans, events or performance are forward-looking statements that involve risks and uncertainties, including risks associated with uncertainties related to contract cancellations, developing risks, competitive factors, uncertainties pertaining to customer orders, demand for products and services, development of markets for the Company's products and services. Readers are cautioned not to place undue reliance on these forward-looking statements, which speak only as of the date hereof. The Company undertakes no obligation to release publicly the result of any revisions to these forward-looking statements that may be made to reflect events or circumstances after the date hereof or to reflect the occurrence of unanticipated events.

All product and service names mentioned are the trademarks of their respective companies.

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