AUTM on the Air

University-industry partnerships often sound straightforward from the outside. A promising discovery is made, a company sees potential, and a collaboration begins. But anyone who has worked inside these agreements knows the reality is far more complex. Research goals, publication timelines, IP rights, background technology, data sources, and internal review processes all have to be understood before a partnership can move forward in a productive way.
My guest today is Dr. Yogesh Sharma, Global Head of External Research Collaboration at Novartis. In this role, he works at the intersection of academic research and corporate R&D, helping shape the structures that allow early-stage research collaborations to succeed. With deep experience in technology transfer, licensing, IP management, alliance governance, research agreements, and term sheet negotiations, Dr. Sharma brings a practical view of what it takes to build partnerships that protect innovation while still allowing science to move.
We talk about how Novartis approaches external research collaboration, where alignment and friction often show up between universities and industry, and why relationships matter just as much as contracts. Dr. Sharma also shares his perspective on background IP, publication review, AI, and data-source diligence, and the importance of keeping the tech transfer office and PI aligned from the earliest stages of a collaboration.

In This Episode:
[01:32] Dr. Yogesh Sharma defines external research collaboration at Novartis as work focused on early-stage research rather than clinical trials, with an emphasis on understanding disease biology and identifying new therapeutic possibilities.
[04:30] Dr. Sharma explains how his background in academic technology transfer helps him understand pressure points on both sides of the table, especially when universities and corporate partners approach collaboration with different needs.
[06:00] The conversation turns to friction around the use of research results, including why Novartis may need flexibility for research programs or regulatory filings while universities need to preserve academic research and publication rights.
[09:11] Dr. Sharma describes the recurring issue of non-exclusive royalty-free licensing and explains why Novartis does not ask for broad rights in every agreement, but may need them when important clinical drugs or pipeline compounds are involved.
[10:27] Strong collaborations depend on more than contract language, with Dr. Sharma emphasizing the importance of trust and communication between the PI and company scientists when research changes direction or results do not go as planned.
[12:39] Dr. Sharma discusses the practical realities of review cycles, publication timelines, and internal approvals at a large company, including the importance of giving industry partners enough time for IP attorney review.
[14:30] Background IP becomes a major focus as Dr. Sharma explains how Novartis may take an option and help cover ongoing patent costs when existing university IP is important to a proposed collaboration.
[17:19] The discussion shifts to AI, platform science, and data ecosystems, with Dr. Sharma noting that AI is already shaping drug discovery, chemistry, target identification, data analysis, and research collaborations.
[19:10] AI collaborations require careful diligence around data sources, existing tools, open-source licenses, and whether any restrictions could limit what Novartis can do with collaboration outputs.
[21:35] Dr. Sharma offers advice to tech transfer professionals, stressing the need for early alignment with the PI around the research plan, diligence, data sources, deliverables, and what each side is bringing into the collaboration.
[23:45] After a deal is signed, Dr. Sharma explains that larger collaborations require continued engagement, project management, kickoff meetings, and a reliable point of contact beyond the PI’s lab.
[25:27] The episode closes with a look at how larger collaborations may involve structured alliance management, while smaller projects are often handled directly by scientists unless a problem arises.

Resources: 
AUTM
Novartis
Dr. Yogesh Sharma - LinkedIn
Novartis Biomedical Research / Novartis Research
Helmholtz Munich Launches Collaboration on AI-Driven Kidney Disease Research

There’s a stretch of time in innovation where things feel the most uncertain, when the science is promising but the path forward isn’t clear and the capital hasn’t quite caught up. It’s a space that can quietly stall even the most compelling ideas. In this episode, the conversation zeroes in on that early stage gap and what it really takes to move something forward when the usual funding sources aren’t ready yet.
My guest today is Teri Willey, founding managing director of Pathway to Cures, the venture philanthropy fund of the National Bleeding Disorders Foundation. Teri has worked across nearly every part of the innovation ecosystem, from leading tech transfer offices to building venture funds and advising investors. That range of experience shapes how she thinks about translation, especially the less obvious pieces that influence whether a deal comes together or falls apart.
We talk about how venture philanthropy works in practice and why it’s becoming an important tool for advancing therapies that might otherwise struggle to find early support. Teri also shares why understanding human behavior can matter just as much as understanding the science, how patient input can change the trajectory of a company, and what tech transfer professionals can do to better align with early-stage investors. It’s a grounded look at how progress actually happens and what it takes to keep it moving.

In This Episode:
[02:17] Teri Willey reflects on her career and the common thread of working between for-profit and nonprofit worlds to commercialize early-stage science.
[03:13] Why science, IP, and funding alone aren’t enough, and how human behavior plays a critical role in getting deals done.
[04:27] Practical advice on managing stakeholder dynamics and keeping negotiations focused on shared outcomes.
[05:12] Defining venture philanthropy and how it differs from traditional venture capital and grant funding.
[06:24] How Pathway to Cures reinvests returns to support future innovation rather than distributing profits.
[07:08] Inside the fund: small team, targeted focus, and leveraging expert advisors and volunteers.
[08:19] Reviewing hundreds of opportunities and acting as both investor and resource for companies in the space.
[09:26] The value of deep scientific advisors and staying close to emerging, sometimes stealth-stage innovations.
[10:53] Where therapies most often stall, especially in the seed and Series A funding gap.
[12:07] Why early patient engagement is critical for clinical success and long-term adoption.
[13:34] The structure of Pathway to Cures and how independence within a foundation enables flexibility.
[14:57] How tech transfer offices can think of venture philanthropy funds as partners or potential licensees.
[16:11] What investors look for and why understanding an investment memo can help TTOs evaluate opportunities.
[17:23] The importance of speed and clarity in licensing negotiations to avoid losing momentum.
[18:49] Strategies for anticipating capital needs across different types of technologies.
[20:16] How IP is viewed as the starting point, not the endpoint, of building a company.
[21:38] Defining success beyond returns, focusing on delivering real therapies and patient impact.
[22:52] The growing role of disease-focused foundations in venture investing.
[24:18] Why traditional investors value foundations for their patient access and domain expertise.
[25:27] How TTOs can better collaborate by engaging early and asking what makes a project investable.
[26:33] What keeps Teri optimistic despite challenges across funding, regulation, and commercialization.
[27:41] Closing reflections on progress, persistence, and the growing impact of innovation.

Resources: 
AUTM
Pathway to Cures
Teri Willey - LinkedIn

Early detection is everything when it comes to Alzheimer’s, but for years, the tools available have made that nearly impossible at scale. Today’s conversation takes a closer look at a breakthrough that could change that equation in a very real way. My guest is Dr. Yuanbing Jiang, also known as Jason, a research assistant professor in the Division of Life Science at the Hong Kong University of Science and Technology. His work sits at the intersection of neuroscience, proteomics, and large-scale data analysis, with a focus on finding practical ways to detect and understand neurodegenerative disease much earlier than we’ve been able to before.
We talk about the development of a 21-protein blood biomarker panel for Alzheimer’s disease, a test that’s reaching about 96% accuracy in detecting early-stage cases and has already been used in clinical settings in Hong Kong. Jason walks through how advances in high-sensitivity proteomic assays made it possible to measure thousands of proteins at once, and why moving beyond a narrow focus on amyloid markers has been key to improving accuracy. We also get into what it actually means to stage Alzheimer’s biologically, not just diagnose it, and how that changes the way clinicians think about treatment timing.
There’s also a broader story here about access and impact. This blood-based approach is faster, less invasive, and significantly more affordable than traditional methods like PET imaging, which opens the door for wider use in different healthcare settings around the world. We discuss what earlier diagnosis means for patients and families, how it could accelerate drug development and clinical trials, and why this kind of innovation is a strong example of what can happen when academic research, technology transfer, and real-world application come together at the right moment.

In This Episode:
[03:47] Jason explains why Alzheimer’s begins developing 10–20 years before symptoms appear and why patients often miss the treatment window.
[04:31] Traditional diagnostics like PET imaging and spinal fluid tests are effective but too expensive or invasive for widespread use.
[05:12] The idea emerges to create a simple blood test that could be faster, cheaper, and accessible to a much broader population.
[06:08] New high-sensitivity proteomic technology makes it possible to measure over 1,000 blood proteins with dramatically improved accuracy.
[06:56] His team identifies more than 400 potential biomarkers and narrows them down to a 21-protein panel for detection.
[07:43] Different biomarkers reveal distinct stages of Alzheimer’s, with immune system changes appearing earlier than neurological decline.
[08:37] The test doesn’t just detect disease, it helps determine what stage a patient is in, which is critical for treatment decisions.
[09:41] Early-stage identification becomes essential as certain drugs only work when intervention happens before major decline.
[11:03] Two key innovations drive the breakthrough: ultra-sensitive detection technology and a whole-body view beyond amyloid markers.
[12:06] Expanding beyond amyloid to include immune, metabolic, and vascular signals improves both accuracy and disease understanding.
[13:02] High diagnostic accuracy reduces misdiagnosis, which can significantly impact patient outcomes and care planning.
[13:58] Validation across Chinese and Spanish cohorts shows the test works consistently across different populations.
[15:02] The blood test reduces diagnostic costs by up to 88%, making early detection more feasible in resource-limited settings.
[16:07] Earlier diagnosis allows patients to access treatment sooner and gives families time to plan and prepare.
[16:53] Blood-based biomarkers streamline clinical trial recruitment by quickly identifying qualified patients.
[17:36] Pharmaceutical companies can now screen large populations more efficiently, accelerating drug development timelines.
[18:22] The next phase focuses on large-scale validation, regulatory approval, and expansion into global healthcare systems.
[19:28] AI is expected to enhance diagnosis, risk prediction, and therapeutic development using biomarker data.
[20:34] Jason shares optimism that earlier detection and better tools could significantly change Alzheimer’s outcomes in the next decade.
[21:12] The conversation closes with the broader impact, and how this innovation could reshape diagnosis, treatment, and patient care worldwide.

Resources: 
AUTM
Yuanbing JIANG - The Hong Kong University of Science and Technology
Yuanbing JIANG - Google Scholar

Most people focus on the breakthrough, but there is a massive gap between a scientific discovery and a product that actually reaches the public. Today, we’re stepping into the "engine room" of one of Africa’s premier research institutions to see how that gap is bridged. My guest is Ravini Moodley, Director of the Technology Transfer Office at Stellenbosch University’s Innovus. She has a background in microbiology and a Master’s in Technology and Innovation Management. She also has the ability to speak both the technical language of the scientist and the strategic language of the market.
At Innovus, she leads a specialized team tasked with finding the "gems" buried within university research and polishing them for the real world. While the broader commercial strategy is set at the executive level, Ravini manages the ground-level pipeline that moves ideas from the lab bench to a functional spin-out. This role requires constant navigation between social impact and economic viability. While ensuring that complex science doesn't just sit on a shelf, but transforms into a solution that can survive a competitive global landscape.
We discuss building a high-functioning TTO and why empathy is the most underrated skill in the field. We also learn why South Africa’s unique geography shapes their strategy. Rather than trying to out-compete institutions like MIT or Oxford in every category, Stellenbosch is doubling down on agricultural and sustainability technologies where they can lead the world simply by connecting the right people. We look at what it takes to turn research into something the world can benefit from.

In This Episode:
[02:27] Ravini walks through the rhythm of her day, from early meetings on contracts and licensing to coordinating closely with research management and her team.
[05:10] Much of the work centers on connecting researchers with industry while balancing reporting, policy review, and the constant flow of new opportunities.
[08:20] Identifying strong IP is both proactive and reactive, with the team building relationships in labs to spot promising ideas before publication.
[11:05] A sustainability case study highlights enzyme-based technology for breaking down bioplastics, developed through a collaboration with the University of Padova.
[14:35] Ravini explains how projects move from disclosure through IP protection and early business analysis before transitioning to the LaunchLab incubator.
[17:42] Empathy plays a key role in guiding researchers, especially when navigating tough conversations around patentability and commercialization paths.
[20:02] While tech transfer challenges are similar globally, South Africa faces unique hurdles due to market size and geographic distance, making global partnerships essential.
[22:00] She shares her excitement around sustainability and agricultural technologies, where local impact can often happen more quickly with the right connections.

Resources: 
AUTM
Ravini Moodley - Stellenbosch University
Ravini Moodley - LinkedIn

One of the biggest shifts in technology transfer over the past decade isn’t just the pace of innovation. It’s the realization that value isn’t created at a single moment. It builds over time, shaped by how well research, intellectual property, and real-world application stay aligned. The challenge isn’t only generating strong ideas. It’s understanding how those ideas evolve, how they’re protected, and whether they ultimately solve problems people care enough about to adopt and pay for.
My guest today is Ram Krishnan, Senior Director of Engineering in Qualcomm’s Government Affairs Group, where he focuses on global IP ecosystem development. Ram's career has taken him across engineering, business, and intellectual property in standards-driven industries such as wireless communications, AI, XR, and autonomous driving. Now he works with universities, startups, and government organizations around the world, focused on how innovation gets taught, protected, and turned into real products and technologies that can actually scale.
We talk about what it means to think about innovation as a full lifecycle rather than a single breakthrough, how strong IP portfolios are built over time, and why the most durable technologies consistently solve meaningful, “pay-for” problems. Ram also shares how industry approaches long-term university partnerships, what signals a tech transfer office is thinking beyond a single transaction, and why early education around IP can change the trajectory of entire ecosystems. It’s a grounded look at how ideas move from research labs into global standards and what makes that journey successful.

In This Episode:
[02:30] How wireless R&D runs on long innovation cycles, where each generation from 3G to 5G builds over time through continuous problem-solving.
[04:15] Ram describes his current work at Qualcomm, focusing on global IP ecosystem development and engaging universities, students, and startups around innovation and entrepreneurship.
[05:55] What successful technologies have in common early on, centering on solving real problems that people are willing to pay for.
[06:57] Looking back at 3G, we reflect on how bringing internet access to mobile phones once felt groundbreaking, even if it seems routine now.
[07:35] We discuss 4G and 5G, and how video, content creation, and network demands evolved with each wave.
[08:25] A look ahead to 6G, where AI and wireless technologies are expected to become increasingly intertwined.
[09:21] IP strategy, with an emphasis on building strong portfolios across the lifecycle rather than relying on single patents.
[11:05] Universities come into the picture, especially their strength in foundational research and the growing need to translate that into commercially useful IP.
[12:35] A deeper look at university relationships shows why long-term, trust-based partnerships tend to outperform one-off engagements.
[14:10] Programs like the Inventors Patent Academy come up as examples of how early education around IP is being built into the pipeline.
[15:45] The balance between standards and proprietary innovation is explored, showing how both play a role in scaling technology globally.
[18:00] In areas like AI and 6G, universities are engaging more deliberately, including increased participation in standards development.
[20:05] Internal alignment across engineering, legal, and business teams is highlighted as a key factor in making external collaborations run smoothly.
[21:30] Strong university partners tend to stay aligned on outcomes and connect their research to real-world problems, even as projects and people change.
[23:03] Expanding a single invention into adjacent use cases comes up as a practical way to build a more valuable and durable IP portfolio.
[24:10] When universities reach out, things like entrepreneurial culture, maker spaces, and spinout track records signal whether there’s real alignment.
[25:45] Ram reflects on lessons learned, especially the importance of being disciplined about IP disclosure before sharing ideas in collaborative settings.
[26:43] Tech transfer works best when it takes a full, 360-degree view from early education all the way through commercialization.

Resources: 
AUTM
Ram Krishnan - LinkedIn
Qualcomm
The Inventor’s Patent Academy