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Source: Thailand Medical News  Dec 11, 2019  3 years, 9 months, 1 week, 3 days, 12 hours, 39 minutes ago

AstraZeneca Announces Collaboration With DeepMatter For AI-Based Compound Synthesis.

AstraZeneca Announces Collaboration With DeepMatter For AI-Based Compound Synthesis.
Source: Thailand Medical News  Dec 11, 2019  3 years, 9 months, 1 week, 3 days, 12 hours, 39 minutes ago
It was announced that AstraZeneca will partner with DeepMatter to improve the productivity and reproducibility of compound synthesis by combining the pharma giant’s automated compound synthesis platform with DeepMatter’s DigitalGlassware™ data collection and structuring technology, through a collaboration whose value was not disclosed.

Glasgow based DeepMatter,is a big data and analysis company focused on enabling reproducibility in chemistry, said that researchers from both companies will team up to strengthen the productivity of synthesizing single compounds and compound libraries.

The project, according to DeepMatter, will be based on unique, structured data harvested via DigitalGlassware, which is designed to allow chemistry experiments to be accurately and systematically recorded, coded, and entered into a shared data cloud.

The technology platform: DigitalGlassware is intended to enable users to capture and analyze information about chemical reactions in compound synthesis including temperature, solvent, and catalysts. A multi-sensor probe sits inside the reaction vessel, providing real-time data including temperature, pressure, UV light levels, and more while an environmental sensor records ambient conditions. Data from external laboratory hardware can also be recorded through software application programming interfaces (APIs).

All structured data are collected and stored in the cloud alongside each process carried out during the reaction, a process meant to contextualize the actions of the user in the lab. Displayed in real-time, the data can be interrogated using multiple views, enabling the analysis of reaction runs and the re-playing of syntheses.

Through capturing in-situ chemical data alongside the experimental intent, observations and outcomes, DeepMatter and AstraZeneca expect that machine learning and AI algorithms could yield cost and time savings while also providing novel insights into drug chemistry.

Michael Kossenjans, associate director, Discovery Sciences, R&D, AstraZeneca, told Thailand Medical News,  “To get potential new medicines to patients faster, we need to reduce the cycle time for lead identification and optimization and look forward to working with DeepMatter to assess the potential of DigitalGlassware to help with this. Our goal is to transform drug design using innovative digital technologies in combination with automation and AI.”

DeepMatter CEO Mark Warne, PhD commented, “We’ve been impressed with the automated chemistry platforms developed at AstraZeneca sites for autonomous delivery of new lead series. We see an opportunity to draw together knowledge from the DigitalGlassware platform to enable machine learning and AI technologies to increase the certainty of producing a high quality and choice of candidate drug molecules.”


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