KTN's online platform helps you to make the connections you need


The Knowledge Transfer Network (KTN) has refreshed its online platform to intelligently connect you to relevant events, funding, thought pieces and specialist staff to help your business innovate and grow.

You can discover content using your area of interest, from Defence Security to transport; from space to health – all major UK economic sectors are covered. Once you have selected your interests, using our intelligent tagging system, we will then display rich and relevant content related to your area, often from surprising sources.

An example might be new satellite technology from the space sector that is applicable in the agri-food sector. KTN-UK.co.uk will help you form these unusual and valuable connections.

All content on the platform has been carefully curated by our team of innovation specialists – not by an automated algorithm – so you can be confident that KTN is connecting you to the most relevant cutting-edge information.


The move also marks a closer alignment with our main funder, Innovate UK , with the website branding making a clear visual link. Knowledge Transfer Network is Innovate UK's innovation network partner, and also works with other funders to provide innovation networking services and fulfil our mission to drive UK growth.

We link new ideas and opportunities with expertise, markets and finance through our network of businesses, universities, funders and investors. From agri-food to autonomous systems and from energy to design, KTN combines expertise in all sectors with the ability to cross boundaries. Connecting with KTN can lead to potential partners, horizon-expanding events and innovation insights relevant to your needs.

Visit our people pages to connect directly with expertise in your sector.

Visit the KTN refreshed online platfom here

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Call document and £6m funding for non-animal technologies now available

The competition document for the current call in developing non-animal technologies is now available, with investment of up to £6m in collaborative R&D projects that support the development and application of non-animal technologies in the UK.

There are limited spaces available for the Manchester and Edinburgh Innovate UK/NC3Rs networking events: For registration for the Manchester event please email events@nc3rs.org.uk , registration for the Edinburgh event can still be done via our website here
Find out more about the collaborative research and development competition and the NAT programme which is supported by Innovate UK, the National Centre for the Replacement, Refinement and Reduction of Animals in Research (NC3Rs), the Biotechnology and Biological Sciences Research Council (BBSRC), the Engineering and Physical Sciences Research Council (EPSRC), and the Medical Research Council (MRC).
The aim is to support projects that will revolutionise the way in which new human and veterinary medicines, agrochemicals and chemicals are assured for effectiveness and safety.  
Proposals must be collaborative and led by a business.
The technologies within scope are:
Biological, tissue engineering and imaging-related
•           stem cell technologies/tissue engineering
•           cell-line technologies
•           cell culture – single-cell-type/3D/mixed-cell type/dynamic (human or animal)
•           organ-on-a-chip/whole-organ models/linked multi-organ systems
•           next-generation sequencing and ‘omics’ – genomics, epigenomics, proteomics
•           technologies for identifying and measuring in vitro biomarkers
•           cell/molecule-level imaging and sensing – positron emission tomography, magnetic resonance imaging, optical, in vitro/ex vivo, high-contrast
•           stratified (personalised) medicine approaches
•           use of non-mammalian organisms or plants
•           high-throughput technologies/combinatorial chemistry
•           micro-structured surfaces and micro-fluidics
•           automation and control
Computational and mathematical methods
•           mathematical modelling
•           computer simulation and in silico modelling
•           structure-activity relationships and computational chemistry
•           data-mining and analysis of large complex (including historical) data sets