D.2 – Transformational Tools and Technologies Project (TTT)

Bio-based innovation in society: supporting the sustainable way of living is sponsored by European Commission — Horizon Europe. Expected Outcome: Project results are expected to contribute to all of the following expected outcomes: advanced socio-economic transformation based on scientific/technological opportunities delivered by the bio-based sectors and bioeconomy. This will result in innovative bio-based products and services, supporting the more sustainable way of living (e.g. new socio-economic models), higher circularity, affordability, resource efficiency, climate neutrality etc); improved public understanding and engagement in bio-based innovation underpinned by scientific advances in life sciences and biotechnology; better living conditions for individuals and communities, benefiting from less polluted ecosystems, via healthier, and environmentally sustainable products and services with a reduced carbon footprint and based on circular and bio-based solutions. Scope: The projects under this topic are relevant to the EU policies related to the European Commission communication on: Building the future with nature: Boosting Biotechnology and Biomanufacturing in the EU, the Strategy for European Life Sciences, the EU Biotech Act, Clean Industrial Deal and the policies related to the fair green transition (objective of not leaving anyone behind). It also contributes to the Start-ups and Scale-ups strategy. Synergies with activities under the Circular Bio-based Europe (CBE) Joint Undertaking and New European Bauhaus are encouraged. Proposals should address the following activities: develop the innovative user-friendly bio-based products and/or services, underpinned by biotechnology and biomanufacturing approaches, to support the more sustainable applications with a clear societal benefit, such as less resource-intensive consumer goods, to reduce environmental and climate pressures. Foresee the necessary links with the digital technologies and tools (e.g., bioinformatics, AI, etc.); assess the potential of new socio-economic models for circular and bio-based systems, integrating aspects of environmental justice, gender equality, diversity and social inclusion, as well as relevant international global best practice, via e.g. societal dialogue/innovation, social impact assessment, involvement and inputs from the social sciences and humanities (SSH); include research and innovation activities to understand and increase the level of current public perception and acceptance, including the benefits / risks, addressing the consumer perspective, market acceptance and understanding of the bio-based innovation, as well as delivering higher understanding of consumption patterns and social demands; foresee the cooperation and feedback loops with industry and authorities, in respect to any new market solutions proposed. The multi-actor approach is encouraged. Proposals should involve SMEs – both as project beneficiaries or external actors - and offer opportunities to newcomers to Horizon Europe Cluster 6, as well as engage with the civil society stakeholders such as NGOs and consumer organisations to advance scale-up and facilitate future market deployment. Cooperation with projects funded under parallel topics such as HORIZON-CL6-2026-01-CIRCBIO-07: Advancing the European bio-based innovation enabled by biotechnology and biomanufacturing concepts is encouraged to maximise synergies, while avoiding overlaps. Cooperation between all projects funded under this topic should also be foreseen, as a specific tasks, with an allocation of resources, for synergies. Proposals should integrate the gender dimension and consider other social categories besides gender (disability, age, socio-economic status, ethnic and/or cultural origin, sexual orientation, etc.), and their intersections. This topic requires the effective contribution of SSH disciplines and involvement of SSH experts in order to produce meaningful and significant effects enhancing the societal impact of the related research activities. International cooperation is encouraged. Technology Readiness Level - Techn Programme areas: Horizon Europe (HORIZON), Global Challenges and European Industrial Competitiveness, Food, Bioeconomy Natural Resources, Agriculture and Environment, Bio-based Innovation Systems in the EU Bioeconomy Keywords: Bio-based products (products that are manufactured using biological material as feedstock) bio-based materials, bio-based plastics, biofuels, bio-based and bio-derived bulk and fine chemicals, bio-based and bio-derived novel materials, Biochemical research methods, Biochemistry and molecular biology, Biodiversity conservation, Bioprocessing technologies (industrial processes relying on biological agents to drive the process) biocatalysis, fermentation, Environmental biotechnology, Environmental engineering, Industrial biotechnology, Materials engineering, Social innovation, Social sciences, interdisciplinary, Sociology, bio-based, bio-product, bioeconomy, biomanufacturing, biomass, biotechnology, fair transition

AI integration in CCSI work practice: catalysing innovation and competitiveness is sponsored by European Commission — Horizon Europe. Expected Outcome: Projects should contribute to all of the following expected outcomes: Insights, recommendations, strategies, guidelines, methods and tools supporting full AI integration in CCSI practices become available to CCSI, policymakers, and stakeholders. Scenarios for co-created solutions tailored to CCSI needs, utilizing quality data and federated data sources, along with digital infrastructures, and inclusive cooperation processes, become available. Generally made available AI-powered and ethically designed solutions, tools and services in several CCSI areas benefit creators, cultural professionals, and society, including persons with disabilities and other specific needs, fostering innovative creative expressions and improving creative business models while preserving and enhancing cultural diversity, and inclusion. By mastering ethical and inclusive AI, CCSI are empowered drivers of culture, innovation, competitiveness and societal wellbeing. Scope: AI technologies are transformative, providing unprecedented opportunities for human creativity, experimentations and co-creations. AI profoundly impacts cultural and creative sectors and industries, changing practices, facilitating new ways of working and making innovative services and products possible. Artists, industry players, and cultural organisations increasingly use AI, for assistance in content creation, production, and management, to predict trends, personalise market content, engage audiences, enhance cultural heritage preservation and accessibility, and many more purposes. Cultural and creative sectors and industries (CCSI) [1] need to fully harness AI's potential to maintain relevance, expand their impact and value, increase competitiveness, and keep their vibrant, inclusive nature. Embracing and co-creating ethical AI solutions tailored to CCSI needs will, among other benefits, enable the automation of low-creativity tasks, allowing to increase focus on high-value activities that enhance creativity and productivity, thus unlocking unprecedented possibilities. Production times and costs can be reduced, market reach expanded, preservation, interpretation and inclusive access to cultural heritage enhanced, and new job categories could emerge. Although several initiatives are on the ground, a comprehensive understanding of enabling frameworks and factors and of what is still lacking in terms of data, standards, infrastructures, computing power, tools, knowledge and capacity for the CCSI to fully embrace the opportunities opened by AI is essential for effectively integrating AI technologies into CCSI practices and workflows. Proposals should assess the current level of AI readiness in the CCSI, investigate the specific barriers to AI adoption in the sectors, and highlight areas where AI can offer the most benefits. In continuous engagement with the sectors, based on the analysis of current practices and through concrete use cases, proposals should produce strategic guidance to extensively and seamlessly integrate AI into CCSI operations, enhancing efficiencies, averting risks, and facilitating cross-sector collaboration. Based on this analysis, they should develop a set of tailored tools designed to address the specific gaps and leverage the opportunities uncovered during the assessment. These tools should be strategically aligned with the sector's needs, ensuring they provide targeted solutions to enhance AI adoption and maximize its potential benefits. They should be scalable, affordable for smaller, less-resourced CCSI actors and accompanied by related documentation and training materials and documentation. Proposals should address one of the following two options, and are allowed to address both: Develop scalable pilots for innovative AI-enabled products and services across diverse segments of sectoral value chains, in cooperation with CCSI. These pilots are expected to address identified gaps in CCSI operations and prioritise solutions that catalyse innov Programme areas: Horizon Europe (HORIZON), Global Challenges and European Industrial Competitiveness, Culture, creativity and inclusive society, Cultural Heritage Keywords: Artificial intelligence, intelligent systems, multi agent systems, Business models, Capacity building, Creativity management, Cultural heritage, cultural memory, Data and image processing, Digitalisation/ICT and cultural heritage, Entrepreneurship, Experimentally-driven research and innovation, High performance computing, Intangible cultural heritage, Knowledge transfer, Machine learning, statistical data processing and applications using signal processing (e.g. speech, image, video), Open innovation, Public administration, Social innovation, Tangible cultural heritage, Trustworthy ICT, Visual arts, performing arts, design, AI adoption, AI integration, CCSI, accessibility, audience engagement, automation, business models, capacity building, co-creation, content creation, creative industries, creative innovation, creators’ rights, cross-sector collaboration, cultural and creative sectors, cultural diversity, cultural inclusion., data-driven creativity, digital infrastructures, digital transformation, emerging jobs, ethical AI, federated data, heritage preservation, inclusive AI, innovation ecosystem, knowledge transfer, market reach, multilingual access, personalization, sustainable creative economy, sustainable models, underserved audiences, upskilling

PAR-26-040 is the National Library of Medicine's standing R01 vehicle for bioinformatics, translational bioinformatics and computational biology, and it is one of the more accessible NIH entry points for AI and machine learning work on biomedical data. The NOFO explicitly names artificial intelligence, machine learning and large-scale computational platforms among the transformative technologies it seeks to leverage for extracting actionable knowledge from vast, diverse and complex biological datasets, and it calls out studies that use AI and ML applications for predictive and analytical bioinformatics research as being in scope. That explicit language is worth noting, because AI-heavy proposals submitted to general biomedical NOFOs frequently draw reviewer objections that the methods work is not the point of the call; here it is. Three structural features make this an unusually practical target. First, it is a parent-style PAR with multiple rolling due dates running from 5 June 2026 through 5 February 2029 and an expiration of 6 March 2029, so there is no single make-or-break deadline and a resubmission has somewhere to go. Second, eligibility is broad - higher education institutions, nonprofits, for-profits including small businesses, state, local, federal and tribal governments, and foreign entities are all eligible, and cost sharing is not required. Foreign institution eligibility in particular is not universal across NIH NOFOs and is a genuine differentiator. Third, clinical trials are optional and human subjects involvement is optional, so purely computational projects are fully within scope rather than being penalised for lacking a clinical arm. The trade-off is budget scale: 250,000 dollars per year in direct costs over at most 4 years is modest for an R01 and rules out large data-generation components. This is a fit for method development, tool building and secondary analysis, not for assembling new cohorts.