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News Article | December 7, 2016

Rainbow Seed Fund, an early-stage venture capital fund focused on promising technologies developed at the UK’s largest publicly-funded research facilities and campuses, today announces that the fund have now leveraged more than £200m to work supporting UK’s most ground-breaking and innovative companies. Since the Fund’s inception in 2002, Rainbow Seed Fund has been investing in the earliest and riskiest stages to create promising technology companies that stem out of engineering and high-quality science research. The Fund has made a significant contribution to the commercialisation of more than 30 high quality science technology start-up companies in sectors such as health, environmental services, international development and security. Rainbow’s portfolio showcases a number of ‘world’s firsts’ ambitions and includes two companies named by the World Economic Forum as ‘Technology Pioneers’ (see below list). Rainbow Seed Fund partners are leading UK public sector research establishments led by STFC (Science and Technology Facilities Council), BBSRC (Biotechnology and Biological Sciences Research Council), NERC and Dstl (Defence Science and Technology Laboratory). The fund is independently managed by Midven. “Securing the first round of finance is notoriously hard for early-stage companies, as is investor willingness to continue to back the most promising companies in further funding rounds,” said Dr Andrew Muir, Rainbow Seed Fund Investment Director. “Rainbow aims to lower this establishment phase hurdle and drive companies towards commercialisation and sustainability, offering strategic support and leveraging private capital to help businesses stand on their own. Our differentiating approach is that we don’t just invest in established teams or developed companies. With a risk appetite that is higher than pure private funds, we get involved at the earliest stages and continue to grow with them as ‘patient capital’ investors.” Rainbow Seed Fund Portfolio: World’s Firsts Two of Rainbow’s portfolio companies, Tokamak Energy and Synthace, have been named World Economic Forum Technology Pioneers, joining the ranks of the world’s most innovative companies. By offering backing at an early stage, Rainbow has a unique opportunity to support the UK’s most promising scientists and help turn their ideas into market-leading companies. A number of Rainbow Seed Fund portfolio companies are being recognised for their ‘world’s first ambitions,’ including: MANUFACTURING / ENGINEERING -- Cobalt Light Systems, a spin-out from Rainbow partner STFC, manufactures and sells innovative instruments and technologies for non-invasive, rapid analysis of materials. This technology has applications in airport security to quickly screen liquid contents like baby’s milk; pharmaceutical materials analysis of capsules, tablets, gels or solutions; and handheld detection devices to analyse hazardous materials, explosives and narcotics. Cobalt won the prestigious MacRobert Award from the Royal Academy of Engineering in 2014. -- Last year, Tokamak Energy garnered a 2015 Technology Pioneer award to accelerate the development of cost-effective, clean energy from fusion within the next 10 years. Tokamak aims to accelerate the development of fusion energy by combining two emerging technologies – spherical tokamaks and high-temperature superconductors. MEDICAL / BIOTECH -- Crescendo Biologics is a biopharmaceutical company discovering and developing potent, highly differentiated Humabody® therapeutics in Oncology. In October 2016, Crescendo signed a deal with Takeda on using its Humabody® technology platform to generate tumour targeting drug conjugates and immuno-oncology therapeutics. The deal has a headline value of up to $790m. -- University College London spin-out Synthace, which provides next generation software and processes to exponentially improve productivity in bioscience, was named as the only UK entrant on the World Economic Forum Technology Pioneer 2016 list. Synthace is developing Antha to automate biological research. Antha brings an engineering approach to biology, making experiments far more efficient, connecting and automating complex equipment and enabling better engineer biology for health, food, energy and manufacturing. The company, is already serving customers across the pharmaceutical, agriscience and industrial biotechnology industries. SOFTWARE / HARDWARE -- Formed in February 2011, Spectral Edge is a UEA spin-out from the same stable as the technology behind Apple’s HDR image processing. Spectral Edge technology enhances images and video by using information outside the normal visible spectrum or applying transformations to that within it. Applications range from medical imaging and surveillance all the way to consumer applications such as enhancing camera images and TV pictures. ENVIRONMENTAL -- International GeoScience Services (IGS), a spin-out from the British Geological Survey, has developed IGS Xplore, a new and innovative mineral prospectivity software system designed for de-risking early-stage decision making in mineral exploration. The software system uses novel, non-GIS based, semantically-driven technology to generate early-stage, value-added prospectivity maps for regions, countries or geological terranes where base geodata exists. IGS Xplore readily identifies early-stage exploration targets, quickly and cost-effectively, for an extensive range of commodities in a wide variety of regional geological environments. -- A spin-out from STFC Rutherford Appleton Laboratory, Oxsensis is pioneering a “new breed” of highly accurate, highly stable optical sensors. Using light to measure heat, temperature and pressure, based upon proprietary intellectual property rights, Oxsensis’ dynamic sensors can be used in extreme environments — like those created by jet engines and power stations — where traditional sensors run out of steam. Better sensors allow power savings, reduced emissions and improved asset risk management. Oxsensis works with blue-chip partner in global markets of national significance — aerospace, power generation, space, nuclear, and oil and gas. SPACE -- Oxford Space Systems (OSS) has developed a new generation of deployable global satellite space structures that are lighter, less complex and lower cost than those in current commercial demand. In September 2016, OSS set a space industry record going from company formation to material design through product design, test and launch of its deployable boom on a cubesat (a type of miniaturized satellite for space research) in under 30 months. OSS is using the mission as a flight opportunity to validate a number of predictions made for its proprietary flexible composite material in the demanding environment of low-earth orbit. Rainbow Seed Fund Milestones -- Helped to create more than 30 high technology start-up companies across sectors such as health, environmental services, international development and security. -- Leveraged more than £200 million of private investment into their portfolio companies. This represents a ratio of over £20 for every £1 invested from Rainbow. -- Over and above co-investment, Rainbow has helped generate wider economic impact in the form of salaries, taxes and economic activity in suppliers. Known as “Gross Value Add” (GVA), this measurement, at £5 of GVA for every £1 invested by Rainbow, shows the benefit of early stage investment and is forecasted to grow substantially as the companies mature and grow. -- The Fund bolsters the UK’s exports – an overwhelming majority of sales in Rainbow companies are overseas and total sales have already reached over £70m. -- Rainbow has helped to create 240+ high value technology-related jobs, a figure that is rising rapidly as the companies in Rainbow’s portfolio accelerate and transition from research into production and sales. -- The Fund has already had four successful exits and has recycled the funds into new investments. About Rainbow Seed Fund The Rainbow Seed Fund is an early-stage venture capital fund dedicated to kick-starting technology companies from great science. We focus on companies based on research conducted in publicly-funded laboratories, located on the Research Councils’ science and technology campuses or working in fields of strategic interest to the UK (such as synthetic biology). The Fund is backed by nine UK publicly-funded research organisations including STFC, BBSRC, Dstl and NERC and the Department of Business, Innovation and Skills (BIS). The Fund, whose portfolio comprises more than 30 companies, holds investments in some of the UK’s most innovative companies in areas as diverse as novel antibiotics, research into Alzheimer’s disease, “green” chemicals and airport security. The Fund has leveraged more than £200 million of private investment from just under £9 million of its own investment and helped create many high-value technology jobs. The Rainbow Seed Fund is managed by Midven, an established venture capital firm with a successful track record of investing in small and medium-sized enterprises. For more information, please visit

Taylor W.R.,UK National Institute for Medical Research | Hamilton R.S.,University of Oxford | Sadowski M.I.,UK National Institute for Medical Research | Sadowski M.I.,Synthace
Current Opinion in Structural Biology | Year: 2013

Recent work has led to a substantial improvement in the accuracy of predictions of contacts between amino acids using evolutionary information derived from multiple sequence alignments. Where large numbers of diverse sequence relatives are available and can be aligned to the sequence of a protein of unknown structure it is now possible to generate high-resolution models without recourse to the structure of a template. In this review we describe these exciting new techniques and critically assess the state-of-the-art in contact prediction in the light of these. While concentrating on methods, we also discuss applications to protein and RNA structure prediction as well as potential future developments. © 2013 Elsevier Ltd.

Sadowski M.I.,Synthace | Grant C.,Synthace | Fell T.S.,Synthace
Trends in Biotechnology | Year: 2016

Building robust manufacturing processes from biological components is a task that is highly complex and requires sophisticated tools to describe processes, inputs, and measurements and administrate management of knowledge, data, and materials. We argue that for bioengineering to fully access biological potential, it will require application of statistically designed experiments to derive detailed empirical models of underlying systems. This requires execution of large-scale structured experimentation for which laboratory automation is necessary. This requires development of expressive, high-level languages that allow reusability of protocols, characterization of their reliability, and a change in focus from implementation details to functional properties. We review recent developments in these areas and identify what we believe is an exciting trend that promises to revolutionize biotechnology. Biological complexity is a barrier to fulfilling the potential of biotechnology. Large numbers of complex experiments are required to overcome this barrier.Performing such complex experiments requires sophisticated software and hardware.New programming languages and software tools for this are developing quickly.Low-cost automation and sensors promise to unlock these techniques for all. © 2015 Elsevier Ltd.

Synthace | Date: 2016-04-26

Computer programs and downloadable computer programs that implement a procedural computer programming language, and a laboratory equipment control language for codifying experimental protocols and biological, biochemical and chemical data; computer programs and downloadable computer programs that implement a procedural computer programming language, and a laboratory equipment control language for defining the physical implementation of the protocols on laboratory equipment including data acquisition; computer programs and downloadable computer programs that implement a procedural computer programming language, and a laboratory equipment control language for collating, storing, displaying and processing such data; computer software for automating biological and life science research and development processes; all the aforementioned goods being for use in biological, biotechnological and life science research and development processes.

Agency: GTR | Branch: Innovate UK | Program: | Phase: Collaborative Research & Development | Award Amount: 157.83K | Year: 2014

The bioscience industry currently relies on a small number of organisms to produce the majority of the recombinant products on the market. A collaboration between two UK synthetic biology Synthace and Synpromics and University College London, this project combines cutting edge computational techniques with multifactorial experimental design to develop a novel toolset that will allow the rapid bootstrapping of novel chassis organisms for synthetic biology. This will enable future processes to use chassis that are far better suited to the industrial conditions they are used under, and accelerate the use of synthetic biology in healthcare, food production, chemicals and energy. Outputs of the tools will be fully characterised to ensure they are fully robust under a range of conditions, making sure that they will be of maximum use to the synthetic biology industry

Agency: GTR | Branch: Innovate UK | Program: | Phase: Feasibility Study | Award Amount: 176.50K | Year: 2013

This project will integrate a number of novel synthetic biology technologies in a demonstration project to rapidly engineer a cellular factory. This includes a novel biopump from UCL which will allow the selective import of a hydrophobic substrate into the cell, where a short synthetic pathway will transform it into a higher value aroma chemical, before the final specialty chemical product is exported from the cell. This short synthetic pathway will be rapidly optimized by a combination of a novel gene expression control technology, RiboTite, from University of Manchester and the statistical optimization technology of Synthace. A successful outcome is expected to both yield a process for the production of a high value specialty chemical, as well as a demonstration of a new methodology for the rapid engineering of a bioprocess.

Synthace | Date: 2016-09-21

Methods, systems and apparatus for performing a biological process are provided, wherein the method comprises implementation of at least one unit operation, and wherein the unit operation is defined according to a standardised element structure, the element structure comprising a plurality of functional section blocks, and wherein the section blocks comprise at least one of the group consisting of: imports; parameters; data; physical inputs; requirements; setup; and execution steps.

Synthace | Date: 2016-09-22

Method, systems and apparatus to determine the suitability of parts or protocols to perform unit operations in the context of a biological process, comprising recording of a user score associated with an instance of use of a protocol or part, wherein the context of the use is recorded along with the rating, and wherein the context is defined as the value of factors that may affect the performance of the unit operation in which the part or protocol was used. The method may be implemented as a web service.

Synthace | Date: 2016-09-20

A method and system for increasing process performance in a biological process comprising at least one process step, the method comprising: (a) an identification phase, in which at least seven factors are identified, wherein a factor is defined as a feature of or within a process that when modified will affect the performance of the process, and wherein the factors are selected from at least one process factor and at least one genetic factor; (b) a factor screening phase, in which individual and combined contributions to process performance of each of the at least seven factors are determined, such that at least one multi-factorial interaction is identified; and (c) a refinement phase, in which higher order interactions that result in an increase in process performance between the at least seven factors are identified and tested. The method may be incorporated within automated laboratory and design of experiment systems.

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