Genedata AG. (6/25/19). "Press Release: Genedata Expands Collaboration with AstraZeneca on Deep Learning for High-Content Image Analysis". Basel.

	Organisation	Genedata AG
	Group	Danaher (Group)
	Organisation 2	AstraZeneca plc (LSE: AZN)
	Group	AstraZeneca (Group)
	Product	high-content screening (HCS)
	Person	Pfannes, Othmar (Genedata 200406 CEO + Founder)
	Person 2	Rees, Steve (AstraZeneca 201712 VP Discovery Biology)

Genedata Imagence automates high-content screening workflows

Genedata, a leading provider of advanced software solutions for biopharmaceutical R&D, today announced a collaboration with AstraZeneca to automate high-content screening (HCS) image analysis using Genedata Imagence®. Genedata Imagence is the industry’s first commercial, HCS instrument-independent solution that applies the deep-learning approach to automate the analysis of HCS images on an enterprise scale. Producing high quality results from new experiments in just a few minutes, without requiring specific image analysis expertise, Genedata Imagence broadens the application of HCS, significantly shortens cycles of assay development projects, and reduces time and cost for the analysis of phenotypic HCS assays. Most recently, Genedata Imagence received the Best of Show Award at the 2019 Bio-IT World Conference & Expo.

With this project, Genedata and AstraZeneca strengthen a long-standing collaboration that garnered a 2018 Bio-IT World Best Practices Award for Informatics & Knowledge Management. This project demonstrated how deep learning can automatically transfer learnings from one assay to another, enabling a rapid set-up of analysis workflows for new assays. The new collaboration focuses on:

a) detecting complex phenotypes with minimum human intervention;

b) making difficult imaging assays more robust by reducing the impact of biological variability; and

c) further reducing time and effort to develop imaging assays.

“Our collaboration with Genedata helps drive the exciting innovations that both companies strive for,” noted Steve Rees, Vice President, Discovery Biology, Discovery Sciences, R&D, AstraZeneca. “The computational workflows we’ve jointly developed have proven to be valuable tools for AstraZeneca. Now, with access to the first commercial version of Genedata Imagence software, our scientists can explore the broad benefits of deep learning in their day-to-day operations.”

“Industry collaborations like the one we have with AstraZeneca are the cornerstones of our success,” said Dr. Othmar Pfannes, CEO of Genedata, “Therefore, we are thrilled to collaborate again with AstraZeneca in advancing our deep-learning approach incorporated in Genedata Imagence. We are committed to establishing AI approaches in biopharma R&D, to make discovery operations more efficient, and ultimately generate better results.”

About Genedata

Genedata transforms life science data into intelligence with a portfolio of advanced software solutions and scientific consulting. With award-winning platforms, combined with deep domain expertise, Genedata enables dramatic increases in productivity and quality of research, development, and production. Founded in 1997, Genedata is headquartered in Switzerland with additional offices in Germany, Japan, Singapore, the UK, and the US.www.genedata.com

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Disclaimer

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.

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Record changed: 2023-06-05