Collaboration with AstraZeneca

RNS Number: 1696W
DeepMatter Group PLC
09 December 2019

DeepMatter Group plc

(“DeepMatter”)

Collaboration with AstraZeneca

DeepMatter announces collaboration with AstraZeneca focused on improving productivity of compound synthesis using digital technologies enabled with machine learning and artificial intelligence

DeepMatter's DigitalGlassware™ data collection and structuring technology to be used alongside AstraZeneca's automated compound synthesis platform

9 December 2019 - DeepMatter today announces a collaboration with AstraZeneca to use innovative digital technologies with the aim of improving the productivity and reproducibility of compound synthesis.

Scientists from the two organisations will work together to improve the productivity of synthesising single compounds and compound libraries based on unique, structured data harvested from the DigitalGlassware™ technology.

The conditions of a reaction, such as temperature, solvent and catalysts, are important to the success of any experiment. DigitalGlassware™ allows users to capture and analyse a rich array of information about their chemical reaction. A unique multi-sensor probe sits inside the reaction vessel, providing real-time data (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).

These structured data are collected and stored in the cloud alongside each process carried out during the reaction, contextualising 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. By capturing in-situ chemical data alongside the experimental intent, observations and outcomes, it is expected that machine learning and AI algorithms could yield cost and time savings whilst also providing novel insights into chemistry.

Michael Kossenjans, Associate Director, Discovery Sciences, R&D, AstraZeneca, said:

"Our goal is to transform drug design using innovative digital technologies in combination with automation and AI. To get potential new medicines to patients faster, we need to reduce the cycle time for lead identification and optimisation and look forward to working with DeepMatter to assess the potential of DigitalGlassware™ to help with this."

Mark Warne, CEO of DeepMatter, said:

“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.

We look forward to progressing this exciting collaboration over the coming months as we continue to maximise the potential of the DigitalGlassware™ platform."

 

For further information, please contact:

DeepMatter Group plc

Mark Warne, Chief Executive Officer

T: 0141 548 8156

Shore Capital (Nominated Advisor and Broker)

Tom Griffiths
David Coaten

T: 020 7408 4050

Alma PR

Caroline Forde
Jessica Joynson
Kieran Breheny

T: 020 3405 0205

deepmatter@almapr.co.uk

 

About DeepMatter Group

DeepMatter's long term strategy is to integrate chemistry with technology, thereby enabling a greater use of artificial intelligence and reaching a point where chemicals can be autonomously synthesised through robotics. In the near term this involves the provision of an integrated software, hardware and artificial intelligence enabled platform, DigitalGlassware™, to scientists across research and process development sectors.

The DigitalGlassware™ platform allows chemistry experiments to be accurately and systematically recorded, coded and entered into a shared data cloud. The platform is designed to enable chemists to work together effectively; sharing the details of their experiments from anywhere and in real- time, so that work is not needlessly duplicated, time and money wasted, and ultimately so new discoveries may be made faster.

Visit: www.deepmatter.io and follow @deepmattergroup

 

 

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