This is the third in a series of articles designed to provide SXSW and LSI USA ’26 attendees and other MedTech professionals with practical considerations for efficiently executing mission-critical life science deals. On March 15, during SXSW, Husch Blackwell’s healthcare team will host two panels, bringing together founders and investors from healthcare, technology, and early-stage companies for candid discussion, practical insights, and plenty of time to connect.

Register here.

Introduction

MedTech startups often validate their technology with academic partners. That makes sense as academic medical centers and research institutions offer what few partners can: sophisticated equipment, leading researchers, strong institutional brands, and access to real patients and real-world testing environments.

Research agreements, data use terms, and publication provisions are what investors and buyers read to evaluate the risk and reward from this collaboration. These agreements are negotiated at the outset and tend to last longer than anyone expected. The early negotiations set a trajectory for the collaboration. They may smooth the path ahead or create potholes and bumps that will need to be navigated.

In this post, we unpack the realities of working with academic medical centers, highlight common data and research pitfalls in clinical research and trial agreements, and offer practical strategies to obtain agreement on how data and research assets will be protected.

I. Academic Medical Center Dynamics: What Startups Need to Know

Universities and their affiliated academic medical centers are uniquely valuable innovation partners. They have sophisticated technology and equipment, specialized researchers, strong brands, and access to patients and real-world testing opportunities that few institutions can match. Many are hungry for new revenue streams to complement traditional sources. Reductions to federal research funding, state and federal budget pressures on education and healthcare, as well as shifting demographics, have led many institutions to pursue additional revenue through commercial innovation.

Look a little closer, however, and other perspectives emerge as well. Universities and their affiliated institutions take a long view—many have existed for over 100 years. They have diverse internal and external stakeholders, which help them endure and adapt over time but also decrease the urgency with which they respond to near-term changes. Academic institutions serve a public function and emphasize their role in the expansion of human knowledge. They may seek the right to publish research findings and insights and share them with the broader community, even when it conflicts with the commercial goals of protecting the confidentiality and marketability of an invention. The Bayh Dole Act allows them to retain patent rights in subject inventions developed with federal funding—subject to reserved federal rights—and that ownership expectation often carries over into collaborations with for-profit partners.

AMC legal structures are varied. Teaching, research, and clinical operations may be housed within one or several legal entities. Names of internal business units and separate legal entities may all be variations on the university name. Outsiders may have trouble differentiating relationships and roles. Research funding agreements may be managed by one office (Sponsored Programs), while IP and licensing agreements may be managed by a different one. (Technology Transfer). Data rights negotiated with the Sponsored Programs office may not be accepted by the Technology Transfer office and may have to be renegotiated. A structure that looks like one partner often operates like several. Getting agreement from the right people—in the right order — matters.

The innovation structures and processes that AMCs have adopted reflect the individual balance they seek to achieve and may not be intuitive to a MedTech startup. Understanding the AMC’s perspective is essential to anticipating issues and avoiding unnecessary impasses. With a shared vision, AMCs and early stage MedTech companies are much more likely to achieve their commercialization goals.

II. What Flexible AMCs Do Better

Universities and AMCs who want to be good commercialization partners:

• Identify the strategic areas where they add the most value —and where they don’t.
• Acknowledge the tradeoffs between academic mission and commercial goals—and determine in advance how flexible they are willing to be.
• Have clear, established processes for technology transfer, sponsored research, and publication review that reflect commercial realities.
• Are prepared to discuss publication delay windows and IP ownership expectations at the outset before either side invests considerable time or resources.

When seeking an AMC partner, a MedTech company may want to remember the often-used maxim that “when you’ve seen one AMC, you’ve seen one AMC.” Questions to ask:

• Am I working with the university itself, a clinical operation, a research organization, or an entity that combines those functions?
• Will I need to work with other AMC components to achieve my goals?
• How does the AMC approach commercialization generally and in my area of interest? Exceptions are possible but can be hard fought and time-consuming to obtain.
• What is the AMC’s standard position on publication delay periods and IP ownership—and how much flexibility does it have?

AMC and startup relationships are most productive when the parties can find “win/win” solutions that advance their shared goals. A MedTech startup with a broader understanding of its AMC partner is positioned to find those “wins.”

III. Clinical Research and Trial Structure: Securing Data and Rights for Sponsors

Data and research rights present differently in the AMC context. MedTech startups can anticipate these differences. Confirming data rights, understanding AMC publication interests, and preparing for investor scrutiny of the data rights and consents will help position the startup for success.

A. Don’t Assume You Own the Data

Clinical trial data ownership is often contested and presents its own unique issues.[1] As a sponsor, don’t assume automatic rights to use or share data. Understand the academic partner’s processes for obtaining consent from patients. Even the most favorable data access terms are only as strong as the underlying informed consent. Ensure your consent forms and agreements anticipate secondary uses, artificial intelligence and machine learning (AI/ML) development, and regulatory sharing. Otherwise, you risk legal and operational roadblocks, even if your contract says you “‘own” the data. For example, if your contract only covers regulatory filings, not AI-based tool development, you may face costly renegotiations and delays.

Key questions to ask about data access and use:

• Do our agreements clearly grant us access to all raw and processed data?
• Are our rights broad enough for regulatory, commercial, and AI/ML uses?
• What steps are required if we want to use the data for new purposes?

B. Publication Timing Can Make or Break IP

Academic researchers are under real pressure to publish. Their career success is tied to it. That incentive does not disappear because a startup has a commercialization timeline. Standard publication review windows of 30 to 90 days are intended to give sponsors time to file patent applications before results are disclosed. In practice, that window is often not long enough. Negotiate publication review rights before the research begins to ensure the parties have clear expectations on this important term.

Key questions to ask about publication rights:

• Do we have the right to review and delay publications to protect IP?
• How much time do we have to review proposed publications before submission?

C. Data Use Restrictions: Avoid Future Handcuffs

Some agreements limit data use to a single indication, restricting your ability to expand or pivot. With AI-enabled devices and continuous monitoring, regulators now expect sponsors to address consent for algorithm updates and new data uses. [2] Modern agreements should require future-proofed consent forms to avoid costly re-consent or delays.

Key questions to ask about data use restrictions:

• Does our agreement limit data use to a specific product or field?
• Can we use data for future research, new indications, or AI?
• Have we negotiated flexibility for data reuse or collaborations?

D. Investor Expectations: No Surprises

Investors scrutinize data rights and consent frameworks during due diligence. Weaknesses can be dealbreakers.

Key questions to ask about investor expectations:

• Do we have broad, exclusive rights to core clinical data?
• Are our consent processes audit-ready and compliant with new regulations?
• Are our data rights clearly documented and transferable?
• What happens to data access if the AMC relationship ends?

Conclusion

You don’t need to become an expert in academia to work with an AMC. You do need to understand how the AMC’s commercialization stance will shape your project—and your exit. Understanding lays the foundation for productive negotiations to protect your business and exit strategy. Early agreements often last longer than expected, and your data and consent terms can become a distinguishing asset or an uncertain risk when it’s time to scale or exit.

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[1] See, for example, Matthew Deutsch, Informed Consent, Tissue Ownership, and the Legacy of Henrietta Lacks: Legal and Ethical Foundations in Human Subjects Research, ABA Health eSource (Oct. 23, 2025) (analyzing the unique informed consent issues that arise with tissue samples).

[2] For a comprehensive checklist of steps that life sciences and digital health companies can take now to address the evolving consent issues as related to secondary uses of data, passive data collection, algorithm changes and versioning, and data sharing, please refer to Kimberly Chew, The Next Pressure Point In Digital Health: Informed Consent, Law360 (Jan. 7, 2026, 6:01 PM), https://www.law360.com/articles/2426314/the-next-pressure-point-in-digital-health-informed-consent.