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Spin-outs and licensing

Technology transfer is managed by the independent company Queen Mary Innovation (QMI). Currently over twenty new licensing arrangements are made per year across Queen Mary, with over 70 disclosures of inventions. Spin-outs created with our academics over the past few years have seen remarkable success, as can be seen from the case studies below. We are keen to expand the development of new spin-outs and licensing activities and are in the process of reviewing our IP policy to ensure that it provides appropriate incentives to researchers to pursue opportunities in these areas.

Queen Mary BioEnterprises (QMB) Innovation Centre

The QMB Innovation Centre opened in 2011. It provides modern laboratory and office facilities for incubating growing biotech companies. One of its main current tenants is , Retroscreen Virology Ltd (see below). The Innovation Centre is within the Whitechapel campus of Queen Mary.

Some case studies of Queen Mary spinouts are described below:

Apatech

Apatech is an award-winning Queen Mary spin-out company, established in 2001 to manufacture and market synthetic bone substitutes, which was acquired by global healthcare company Baxter International Inc. for total consideration of up to $330 million.

ApaTech was formed at Queen Mary’s Interdisciplinary Research Centre in Biomedical Materials with an initial investment of £3 million (3i). In 2009 ApaTech was ranked number two in the Sunday Times Tech Track 100 Fastest Growing Private Medical Technology Companies listing and received a number of awards including North America Device Biologics Company of the Year at the Frost & Sullivan Excellence in Medical Technologies and Life Sciences Conference 2009 in recognition of its outstanding commercial success in the US orthobiologics market.  In 2008 ApaTech received the Research and Development Award at the Tech Track awards ceremony in London, in recognition of the innovative and ground breaking research which has underpinned the successful growth of the company. ApaTech also won the Business Initiative Award at The Times Higher Education Supplement awards in 2007.

hVIVO

hVIVO is one of London's largest biotech companies and Europe's leading anti-viral research organisation. It is based in our bio-incubator QMB and had a market capitalisation in 2013 of ~£160m.

hVIVO (originally known as Retroscreen Virology Ltd) was incorporated in 1988 as a spin-out company from Queen Mary, to commercialise the academic research of Professor John Oxford in the field of retroviruses. One of its main approaches is the Human Viral Challenge Model, using human subjects in quarantine to test therapeutics. hVIVO has undertaken over 25 such studies. It also does pre-clinical testing and virustatic testing.

Monoidics

Monoidics is a start-up led by Professor Dino Distefano from the School of Electronic Engineering and Computer Science. The company uses code verification software in order to determine whether a piece of software will execute correctly. It is based on research by Professor Distefano, who with two colleagues developed "Infer", a program which could point to critical flaws such as memory leaks - which can make programs and computers crash. Monoidics was bought by Facebook in 2013 for an undisclosed sum.

Activiomics

Activiomics is a start-up from Barts and The London School of Medicine and Dentistry, based on a novel method of analysing and interpreting cell signalling pathways. This technology enables the pharmaceutical and biotechnology industry to identify biomarkers and better select new drugs for diseases such as cancer, autoimmunity and diabetes and help reduce their time to market. A number of investments in the company have been made, eg by IP Group, and the company continues to grow.

Other examples

There are a wide variety of other QM start-ups at various stages of growth – two examples are Actual Experience, which provides improvements to applications delivered across global digital supply-chains, and Chatterbox, whose expertise is in the emotional sentiment analysis of text through machine learning and natural language processing. 

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