In Conversation With: The NIH

Could you briefly introduce yourself, your role, and your experience within the 3D Tissue Modelling?

I currently serve as the Director of the NIH Standardized Organoid Modeling (SOM) Center, where I lead efforts to establish a national foundation for organoid standardization, validation, and integration into translational research. My work sits at the intersection of experimental biology, engineering, and clinical application, with over 20 years focused on developing human-relevant in vitro systems, including primary cell platforms, organoids, and microphysiological systems.

My experience spans academia, industry, and government. I served as a tenured faculty member where I founded and led an academic research lab focused on biomimetic disease models and precision medicine applications, while also mentoring over 60 trainees across graduate and undergraduate programs. I also founded a startup company to translate NAMs into scalable technologies, bridging innovation with real-world application.

Across all of these roles, my focus has been consistent: how do we move these models from being scientifically impressive to being reliable, reproducible, and decision ready. NIH SOM is the next step in that trajectory-scaling that thinking into a coordinated, NIH-wide infrastructure aligned with regulatory science and public health priorities.

 

What do you believe are the three biggest barriers preventing full adoption of complex in vitro models, and how do you think we can begin overcoming them?

First, lack of standardization.
Protocols vary significantly across labs, which means the same model behaves differently depending on where it’s generated. That breaks comparability.

Second, absence of clear validation frameworks.
We don’t consistently define what ‘working’ means. Without fit-for-purpose validation tied to specific use cases, these models remain difficult to trust-especially for regulatory or clinical decisions.

Third, fragmentation across stakeholders.
Academia, NIH, industry, and regulators are not aligned early enough. We often try to retrofit validation and regulatory relevance after the fact.

The recent FDA guidance on NAMs makes this very clear. The bar is not innovation-it’s validation, reliability, and context of use. These systems will only be adopted if they are at least as informative and dependable as existing approaches.

How do we address this?
We stop treating this as isolated innovation and start treating it as infrastructure. That means standardization, shared benchmarks, and early alignment across stakeholders. That is exactly what NIH SOM is designed to do.

 

What excites you most about the NIH’s new Standardized Organoid Modelling (SOM) Center?

What excites me most about NIH SOM is that it addresses the problem the field has been avoiding.

We are not building another model. We are building the foundation that makes all models usable.

That includes:

• Defining fit-for-purpose validation frameworks
• Integrating AI/ML to optimize protocols and quantify performance
• Establishing reference systems and benchmarks
• Aligning early with regulators, industry, and clinical stakeholders

This is particularly important in light of the FDA’s recent guidance. The expectation is clear-these systems must be validated, reproducible, and decision-relevant. NIH SOM is intentionally designed to meet that expectation from the start.

We are also structured as a neutral hub in a foundation-building phase. We are engaging the community early to understand where there is real scientific and clinical overlap and using that to inform how we design and validate these systems.

If we get this right, organoids stop being promising tools and become trusted platforms that can inform real decisions.

 

Why do you think it’s important for the field to come together at the 11th 3D Tissue Models Summit this year?

Meetings like the 3D Tissue Models Summit are important because the field is still largely operating in silos.

Everyone is making progress-but not in a coordinated way.

If we want these models to be adopted broadly-by NIH, by industry, by regulators-we need alignment on:

• What success looks like
• How performance is measured
• What data are considered decision-relevant

The regulatory landscape is also shifting. With FDA signaling clear expectations for NAMs, the field needs to move quickly from capability to credibility and standardization.

This summit is an opportunity to have those conversations directly with the people who are building, using, and evaluating these systems.

From an NIH SOM perspective, this is exactly the type of engagement we need-early, honest, and grounded in real use cases.

 

What are you most looking forward to as an attendee at this year’s summit? Any particular sessions?

I’m most interested in discussions that move beyond capability and into credibility and adoption.

Specifically:

• Sessions focused on validation and benchmarking frameworks
• Discussions around regulatory integration and context-of-use
• Examples where these models have been used to inform real decisions-not just generate data

I’m also looking forward to engaging directly with investigators, industry partners, and regulators to understand where the real friction points are. That input is essential for NIH SOM. We are in a foundation-building phase, and how we design this system depends on understanding those gaps clearly.

For us, it’s not just about attending-it’s about listening and integrating what we learn into how we build the system.