DeepMatter Group PLC DeepMatter collaboration with AstraZeneca
09 12월 2019 - 4:00PM
RNS Non-Regulatory
TIDMDMTR
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(TM) data collection and
structuring technology to be used alongside AstraZeneca's automated
compound synthesis platform
09 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(TM) technology.
The conditions of a reaction, such as temperature, solvent and
catalysts, are important to the success of any experiment.
DigitalGlassware(TM) 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(TM) 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(TM) 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(TM) platform."
For further information, please contact:
DeepMatter Group plc T: 0141 548 8156
Mark Warne, Chief Executive Officer
Shore Capital (Nominated Adviser and
Broker) T: 020 7408 4050
Tom Griffiths
David Coaten
Alma PR T: 020 3405 0205
Caroline Forde deepmatter@almapr.co.uk
Jessica Joynson
Kieran Breheny
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(TM), to
scientists across research and process development sectors.
The DigitalGlassware(TM) 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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END
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