Technology Transfer Models

𝗧𝗵𝗲 𝗙𝘂𝘁𝘂𝗿𝗲 𝗼𝗳 𝗧𝗲𝗰𝗵 𝗧𝗿𝗮𝗻𝘀𝗳𝗲𝗿: 𝗔𝘀𝗵𝘄𝗶𝗻 𝗥𝗮𝘃𝗶𝗸𝘂𝗺𝗮𝗿 𝗼𝗻 𝗖𝗘𝗥𝗡 𝗩𝗲𝗻𝘁𝘂𝗿𝗲 𝗖𝗼𝗻𝗻𝗲𝗰𝘁 𝗮𝗻𝗱 𝗔𝘁𝗼𝗺 𝗙𝗮𝗰𝘁𝗼𝗿𝘆 Last week on Nothing Ventured, I spoke to Ash Ravikumar, a professional in science entrepreneurship with immense experience in commercialising advanced technologies. He served for 5 years as an Entrepreneurship Development Officer at CERN, where he designed and launched CERN Venture Connect, a platform aimed at bridging science with industry through standardising licensing agreements and facilitating spinouts. Ash has held key roles in organisations such as UniQuest, the University of Melbourne, and Honeywell, focusing on technology transfer, business development, and commercialisation. Ash’s passion lies in material science, IP strategy, and fostering innovation at the intersection of science and entrepreneurship and he is building Atom Factory to accelerate tech transfer globally. We talked about: ↳ The Importance of Making Science Accessible: Ash discussed how science has become too academic and elitist, often leaving the general public disconnected from its wonders. He talked about the need to bridge this gap by making scientific knowledge more accessible and enjoyable for everyone, not just academics. This is crucial for inspiring the next generation of scientists and innovators. Let's shift the narrative from memorising equations to fostering curiosity and understanding science better! ↳ Rethinking Tech Transfer Models: During his time at CERN, Ash developed the Venture Connect program, which revolutionised the approach to tech transfer. Instead of focusing on capturing equity, he prioritised speed and efficiency in getting technologies into the hands of startups. By standardising licensing agreements and minimising barriers, Ash showed that the goal should be to facilitate innovation rather than control it. This approach could serve as a model for universities and research institutions worldwide, encouraging them to focus on the impact of their inventions rather than just financial returns. ↳ Building a Distributed Manufacturing Ecosystem: Ash's vision for Atom Factory is nothing short of groundbreaking. By leveraging existing university resources and equipment, he aims to create a decentralised marketplace for manufacturing that allows researchers to scale their innovations from milligrams to kilograms without the heavy capital expenditure typically required. This model not only supports academic research but also accelerates the commercialization of new materials, making it easier for startups to prove their concepts and attract investment. Subscribe and rate wherever you get your podcasts! YouTube: https://lnkd.in/dhyJD6rF Spotify: https://lnkd.in/dNKkeyCB Apple: https://lnkd.in/dxhV5yXP

I am thrilled to see this announcement from the National Science Foundation (NSF) on how we translate research into public benefit, which acknowledges an important consideration: that different institutions and IHEs have different capacities to do this. This new program creates tiers for entry and prioritizes research mobilizations, knowledge dissemination, engagement, and commercial tech transfer. The gap between academic discovery and tangible public solutions is one of the most significant opportunities in the U.S. innovation ecosystem. The U.S. National Science Foundation (NSF) and the Directorate for Technology, Innovation and Partnerships (TIP) have released an updated solicitation for the Accelerating Research Translation (ART) program. The goal is clear: build capacity for translational research at Institutions of Higher Education (IHEs) across the nation, not just in established tech hubs. What is distinctive about this approach? The NSF is moving beyond the traditional "tech transfer" metrics of just patents and startups. They are looking for Research Translation Readiness Levels (RTRL). Whether an institution is just starting to build infrastructure or is ready to mentor others, there is a specific track designed to meet them where they are. The 5 Tracks for Funding: 🚀 Track 1: Accelerating Technology Transfer (ACT) For: IHEs with low-to-medium readiness but high potential. Goal: Build the initial infrastructure for innovation. Funding: Up to $3M (3 years) 🌱 Track 2: Growing Capacity (GROW) For: IHEs with high research volume but low translation outcomes. Goal: Partner with a mentor institution to unleash innovation potential. Funding: Up to $6M (4 years) 🤝 Track 3: Technology Transfer Resource Centers (RESOURCE) For: High-readiness IHEs or non-profits. Goal: Launch regional centers to support other institutions with guidance and services. Funding: Up to $8M (4 years) 📚 Track 4: Education and Training (ET) For: Organizations with established ecosystems. Goal: Develop and deploy national training materials for entrepreneurship and translation. Funding: Up to $3M (3 years). 🔗 Track 5: Coordinating Center (CART) For: A unifying center to coordinate efforts across all tracks. Goal: Monitor progress and facilitate integration. Funding: Up to $3M (5 years) This is a massive step toward democratizing innovation and ensuring that research dollars translate into sustained economic and collective impacts for our communities. #NSF #ResearchTranslation #HigherEd #Innovation #TechTransfer #PublicImpact There's an ART in that :) https://lnkd.in/ettWKtQX

#TeachMeTuesday | How do we move from excellent public research to measurable innovation and impact? That’s the challenge many research organizations face – and this week’s #TeachMeTuesday looks at a very concrete example: how Fraunhofer-Gesellschaft redesigns its business models to make technology transfer systematic and impactful. The (German) article by Oliver Gassmann and Marc Tobias in Wissenschaftsmanagement 2025 digs into that question – with lessons that are relevant for research institutes, TTOs and universities. https://lnkd.in/ega7yi8p 1️⃣ Academic lessons: what the paper contributes 1. Business models as the “missing middle” We often talk about national innovation policy on one side and individual research projects on the other. This piece focuses on the organizational level in between: how a public research organization designs its business models so that contract research, licensing and spin-offs actually deliver impact. 2. Beyond “Happy Engineering” The authors highlight a familiar European pattern: strong technology, weak business model adaptation. 3. Many transfer channels, one underlying logic Instead of treating contract research, licensing, spin-offs, training, data services, etc. as separate worlds, business models need to integrate them into one. 2️⃣ Practical lessons for research leaders & TTOs 1. Work with two business-model levels The authors distinguish between: - Corporate / system-level models – how the organization as a whole creates and captures value. - Technology-level models – how individual institutes translate that into concrete offerings around specific technologies and infrastructures. 2. Make the “magic triangle” explicit Four simple questions: Who is the real customer / stakeholder? What is the precise value proposition? How is it delivered – including partners, infrastructure, data? How is value captured – within public-law and funding constraints? 3. Treat rules as design constraints, not excuses State-aid law, funding rules and public accounting limit certain options – but they don’t forbid business model innovation. There is still room for: New transfer patterns Smart combinations of public and private funding Spin-offs where only a private entity can fully exploit the model 4. Test business models early, not at the end 3️⃣ Why this matters for Europe Fraunhofer’s dual mission – serving society and strengthening industrial competitiveness – is emblematic of many European public research organizations. see also World Intellectual Property Organization – WIPO's Harnessing Public Research for Innovation in the 21st Century, https://lnkd.in/epmBQV3H

How do we turn excellent research into real impact? For more than a decade I’ve had the privilege of coaching research managers of Fraunhofer-Gesellschaft on business models and technology transfer. Together with Marc Tobias (Fraunhofer Headquarters), I’ve now distilled many of these experiences in a new (German) article in Wissenschaftsmanagement 2025. Using the St. Gallen Business Model Navigator, we explore how research organizations like Fraunhofer can: - Think beyond projects and funding lines and instead design systematic business models for contract research, licensing and spin-offs - Use 66 proven business model patterns (e.g. Pay-per-Use, Solution Provider, Freemium, Lock-in) to shape new transfer paths for technologies and infrastructures - Work with the “magic triangle” (Who is the customer? What is the value proposition? How is it delivered? How is value captured?) to bridge public mission and entrepreneurial responsibility - Follow our four-step process from ecosystem analysis to ideation, integration and real-world testing of new models. Our core message: Technological excellence alone is not enough. Only when knowledge, ideas and technologies are translated into viable business models do they create sustainable economic and societal value – for Fraunhofer, for industry partners, and for Europe as an innovation space. The article is particularly relevant for research institutes, technology transfer offices and universities that want to move “from insight to impact”. If you work in this space and are interested in applying business model thinking to your research environment, my colleagues from Seconds (formerly BMI Lab) and myself are happy to exchange ideas. #BusinessModelInnovation #TechnologyTransfer #Fraunhofer #ResearchImpact #BusinessModelNavigator #InnovationManagement #RT