e-Therapeutics plc Notice of Interim Results (9786A)
September 17 2018 - 6:30AM
UK Regulatory
TIDMETX
RNS Number : 9786A
e-Therapeutics plc
17 September 2018
E-THERAPEUTICS PLC
("e-therapeutics" or the "Company")
NOTICE OF INTERIM RESULTS
Oxford, UK, 17 September 2018: e-therapeutics plc (AIM: ETX),
the network-driven computational drug discovery company, will
announce its interim results for the half-year ended 31 July 2018
on 4 October 2018.
For further information, please contact:
e-therapeutics plc Tel: +44 (0) 1993 883 125
Ray Barlow, Chief Executive Officer www.etherapeutics.co.uk
Steve Medlicott, Finance Director
Numis Securities Limited Tel: +44 (0) 207 260 1000
Michael Meade/Freddie Barnfield (Nominated www.numis.com
Adviser)
James Black (Corporate Broking)
FTI Consulting Tel: +44 (0) 203 727 1000
Simon Conway/Brett Pollard etherapeutics@fticonsulting.com
About e-therapeutics
We are an Oxford, UK-based company with a unique and powerful
computer-based drug discovery platform and a specialised approach
to network biology.
Our novel network-driven methodology allows us to discover new
and better drugs in a more efficient and effective way.
We use our highly productive drug Discovery Engine to develop
our own IP-protected, preclinical drug discovery programmes which
will be of interest to partners looking to acquire or in-license
novel and differentiated assets. We are currently developing two
programmes in immuno-oncology and have a number of partner-ready
projects in areas such as fibrosis and tumour microenvironment.
Because of our novel network-driven drug discovery ("NDD")
approach, we believe there is potential to enter into several
different types of collaborative partnerships with biotech, pharma
and other technology companies to create sustainable mutual
value.
About Network-Driven Drug Discovery ("NDD")
e-Therapeutics' proprietary NDD platform comprises a suite of
powerful computational tools to augment and interrogate the vast
amount of biological information currently available in both public
and private databases.
Our NDD platform is founded on sophisticated network science and
employs techniques such as machine learning, artificial
intelligence and state-of-the-art data analysis tools. Using our
biological expertise, we can create and analyse network models of
disease to identify likely proteins that could effectively be
disrupted to treat the disease.
We believe that our network-driven approach more realistically
reflects the true complexity of disease, with its multiple and
often interconnected cellular pathways. By modelling and analysing
disease networks and considering the pattern of connections between
proteins, and not just single pathways, we more efficiently select
the very best drug-like compounds for screening and for subsequent
medicinal chemistry and pre-clinical testing. With our novel
methodology, significant numbers of active molecules can be
identified and tested quickly. Our approach is highly productive
and consistently generates hits that have been progressed into
potent, selective and novel drug molecules.
Our overall aim is to discover more efficacious drugs more
effectively. By using more biologically realistic, cell and
tissue-based assays we can choose and design compounds that are
more likely to translate into better, more clinically efficacious
drugs.
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of this information may apply. For further information, please
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END
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