9th Dec 2019 09:15
(Alliance News) - Shares in software firm DeepMatter Group PLC more than doubled on Monday, after the software firm said it will be collaborating with pharmaceutical giant AstraZeneca PLC in a digital technology venture, designed to speed up the drug delivery process.
Deepmatter's stock leapt 78% to 3.65 pence each in London on Monday morning. Astra shares were down 0.5% to 7,222.00p.
As part of the collaboration, Astra will assess Deepmatter's DigitalGlassware platform, which enables chemists to share the details of their experiments from anywhere and in real-time.
Michael Kossenjans, an associate director at Astra's Discovery Sciences, Research & Development unit, said: "Our goal is to transform drug design using innovative digital technologies in combination with automation and artificial intelligence. 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."
DeepMatter Chief Executive added: "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 artificial intelligence 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."
DigitalGlassware works by placing a sensor in a chemical reaction vessel, allowing it to monitor changes in temperature, pressure and UV light levels. The platform also has another probe, which monitors existing environmental conditions.
DeepMatter explained: "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 artificial algorithms could yield cost and time savings whilst also providing novel insights into chemistry."
By Eric Cunha; [email protected]
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