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Evonetix named Best Synthetic Biology Company at OBN Awards

publication date: Oct 25, 2018
 | 
author/source: EVONETIX LTD

EvonetixPrestigious business award granted in recognition of novel gene synthesis technology

EVONETIX LTD, the Cambridge-based company pioneering an innovative approach to scalable and high-fidelity gene synthesis, has received the award for “Best Emerging Synthetic Biology Company” at the 10th Anniversary of the Oxford Bioscience Network (OBN) Awards, in recognition of the Company’s novel gene synthesis technology, and its potential to facilitate the rapidly growing field of synthetic biology.

The OBN Awards, one of the UK life science industry’s most prestigious awards evenings, reported a record increase in entry numbers, with entries up an impressive 48% on last year’s total. Over 300 delegates attended the event, which recognise and celebrate the most inspiring and innovative UK-based companies across biotech, medtech, imaging, digital and synthetic biology. The Awards took place at the Oxford Examination Schools, an historical Grade II listed venue.

By directing the synthesis of DNA at many sites in parallel, followed by an integrated error-detection process throughout assembly, Evonetix’s platform facilitates the synthesis of high-fidelity, long DNA molecules at scale, including challenging sequences with high GC-content or repeats. The Company’s approach to gene synthesis has the potential to enable many applications in the rapidly growing field of synthetic biology, from the development of novel pharmaceuticals, to industrial biotech, renewable fuels, agriculture and potentially digital data storage.

Tim Brears, Evonetix CEO, said: “It is a huge honour for our de novo gene synthesis technology to be recognised for its potential impact on the exciting and fast-growing synthetic biology field. At Evonetix we are focused on further advancing our technology to address the need for scale and high fidelity, and this accolade is testament to the significant progress we have made.”




 

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