The Art (and Science) of Matrix Selection: 5 Expert Tips from Inventia Life Science’s Whitney Symons

For researchers transitioning to 3D cell culture, selecting the right matrix can feel like a high-stakes puzzle. The goal is simple: replicate the native environment of the tissue you're modeling. But with so many variables—stiffness, composition, cell type, assay requirements—how do you know you’re making the right choice?

According to Whitney Symons, Customer Success Manager at Inventia Life Science, the key is thinking of the matrix as more than just a scaffold.

“It’s the microenvironment that shapes everything from cell behavior to experimental outcomes,” she explains. “A good match doesn’t just support cell growth—it sets the stage for more reproducible, meaningful biology.”

In this post, Whitney breaks down her approach to matrix selection, offering tips and insights for getting it right from the start.

Why the Matrix Matters

In traditional 2D culture, cells grow on flat, rigid surfaces that fail to capture the complexity of real tissues. The shift to 3D models aims to solve that problem, but only if the matrix is well matched to the biology.

“A 3D model is only as good as the environment you put it in,” says Whitney. “The matrix determines everything from how cells adhere and interact to how they respond to drugs or migrate through the tissue.”

With RASTRUM™ users can choose from a growing library of tunable matrices, each formulated with synthetic PEG-based hydrogels designed to replicate key biophysical and biochemical aspects of human tissue. From epithelial models to stromal-rich co-cultures, there’s flexibility to suit a wide range of research goals.

RASTRUM Matrices are modular by design, and each matrix formulation can be tuned by combining three key elements:

• Bioactive peptides (e.g., RGD, YIGSR, GFOGER, or CNYYSNS) to engage integrins and other cell surface receptors
• Matrix stiffness, spanning soft to stiff conditions to replicate tissue-specific mechanical cues
• Optional additives, such as full-length proteins (fibronectin or laminin) and hyaluronic acid (HA), to further mimic features of the native extracellular matrix (ECM)

This flexibility enables researchers to recreate a range of tissue environments—from soft, brain-like matrices to fibrotic or stiffened tumor conditions—without relying on animal-derived components like Matrigel.

But with all this flexibility comes decision-making. That’s where Whitney and the Inventia Life Science team come in.

“Matrix selection is a conversation,” Whitney says. “We guide each customer based on their cells, their biology, and their goals. No one has to do this alone.”

Tip 1: Start with the Biology and K.I.S.S. (Keep It Simple, Scientist!)

When it comes to matrix selection, biology should always come first.

“Always begin with the tissue type you’re trying to model,” Whitney advises. “Think about what that tissue looks and feels like in the body—what’s its stiffness? What are the dominant ECM proteins? Is it highly vascularized or immune-infiltrated?”

This foundational thinking is especially important when working with a new cell type or disease model. A soft, laminin-rich matrix may be best for neural models, while stiffer, collagen-based environments could better support fibroblasts or tumor–stromal co-cultures. If you're not sure where to start, Whitney recommends looking at the literature, histology references, or even your own IHC data to identify the ECM cues most relevant to your biology.

That said, don’t overengineer it.

“One of the most common pitfalls is trying to do too much too soon,” Whitney says. “We usually start customers with three matrix formulations—a tri-peptide base at different stiffness levels, and if needed, one with an additive like hyaluronic acid or a full-length protein.”

This kind of controlled comparison helps researchers quickly identify what supports cell viability and morphology without introducing unnecessary variables. From there, the model can evolve as needed.

Whitney’s go-to analogy? “Matrix selection is like building a burrito. You start with your base—stiffness—then layer on your peptides, and only add toppings like HA or proteins if your cells really need it.”

In other words: understand your biology, choose a clean starting point, and build complexity only as the science requires it.

Tip 2: Consider Your Tissue Type

The matrix should reflect the biological environment you're trying to mimic. That means selecting formulations based on the physical and biochemical characteristics of your target tissue. For example, soft matrices are often best suited for tissues like brain, lung, or adipose, while stiffer matrices can help recreate the architecture of cartilage, fibrotic tissues, or solid tumors.

Peptide selection matters too. GFOGER mimics collagen I, a major component of connective tissues, whereas CNYYSNS is derived from collagen IV, which is prevalent in basement membranes. By matching stiffness and peptide composition to the natural ECM of your tissue type, you can design a model that better captures the native biology.

“Choosing the right peptides and stiffness helps your model ‘feel’ more like the tissue it’s meant to represent,” Whitney notes. “That’s critical for capturing authentic cell behavior.”

Tip 3: Know Your Cells

Your cell source can greatly impact matrix compatibility. Primary cells and stem cells tend to be more sensitive and may require a matrix with extra support, such as full-length proteins or HA. Immortalized cell lines are typically more robust and may thrive in a simpler tri-peptide base.

A PrintRun™—A RASTRUM Cloud-designed process that defines the parameters for printing including matrix composition and stiffness, 3D cell model architecture and plate layout—is especially helpful here

“We look at cell morphology, proliferation, viability, and key markers across conditions,” she explains. “It’s often easy to spot a clear winner. You’re looking for good growth, consistent architecture, and expression of your key markers.”

The beauty of RASTRUM is that it allows rapid iteration without high cell burden. You can test multiple conditions in parallel, optimize quickly, and move forward with confidence.

Tip 4: Focus on Your Research Question

Matrix selection isn’t just about replicating biology—it’s about supporting the outcomes you care about. Are you modeling fibrosis or tumor invasion? Studying immune infiltration or epithelial barrier formation?

“The matrix should support your experimental goal,” Whitney explains. “That might mean increased stiffness to mimic fibrosis or a more porous matrix to allow immune cell infiltration.”

With RASTRUM, researchers can test the same cell type in different matrices to compare responses—powerful for screening, mechanistic studies, or hypothesis generation.

The matrix can even evolve with the workflow. Some users start with one formulation for cell expansion and then switch to another for drug screening or imaging, depending on the endpoint.

Tip 5: Use Your Support System

Matrix selection can feel daunting at first. But RASTRUM customers aren’t expected to figure it out on their own.

“We don’t just drop off an instrument and disappear,” Whitney says. “Our customer success, applications, and tech support teams are here to collaborate with you. Whether it’s optimizing conditions, troubleshooting results, or designing a new model. We’re in it together.”

Inventia Life Science also maintains an internal knowledge base with performance data from previously validated applications. For new use cases, Whitney and her colleagues help develop a plan, suggest starting points, and guide researchers through the optimization process.

“RASTRUM isn’t just a tool,” Whitney adds. “It’s part of a partnership. We want your cell models to work, and we’re here to make that happen.”

Final Thoughts

Matrix selection is part science, part strategy. And with the right tools and guidance, it doesn’t have to be intimidating.

With RASTRUM’s tunable matrices and expert support from Inventia Life Science’s team, researchers can build 3D models that are both biologically relevant and ready for downstream applications. Whether you’re just getting started or optimizing your next co-culture assay, remember: your matrix matters.

“It’s not about picking the perfect matrix the first time,” Whitney says. “It’s about starting smart, learning fast, and building models that work for your science.”

Want to learn more about RASTRUM Matrices?

Want to dive deeper into how Inventia Life Science’s Matrices support 3D cell culture success?

Explore our Matrices page ➝

Download the application note: Tunable matrices for biologically relevant 3D models ➝