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What are NAMs?
NAMs is an umbrella term for modern methods that can reduce, refine, or replace animal testing by generating data that is more directly relevant to human biology.
The FDA’s Roadmap to Reducing Animal Testing in Preclinical Safety Studies describes a stepwise plan to reduce animal testing by using scientifically validated NAMs, including organ-on-a-chip systems, computational modeling, and advanced in vitro assays. It also highlights a key motivation: over 90% of drugs that appear safe and effective in animals do not ultimately receive FDA approval in humans, largely due to safety and/or efficacy issues.
The FDA roadmap groups NAMs broadly into:
- In vitro human-derived systems (including organoids and microphysiological systems)
- In silico tools (computational modeling, AI/ML, PBPK)
- Other innovative approaches (ex vivo tissues, high-throughput screening, etc.)
In practice, NAMs are not “one model.” They are a toolbox. The most effective strategies often combine multiple NAMs to answer different questions—safety signals, mechanism, dose selection, and translational confidence.
The main model families: organoids, 3D tissues, MPS, and organ-on-a-chip
If you’re entering the field, the terminology can feel crowded. Here’s a simple way to map the landscape.
1. 3D tissue models (a broad category)
3D tissue models describe any in vitro system where cells are organized in three dimensions rather than as a flat monolayer. This category can include spheroids, engineered tissues, organoids, and some MPS setups.
Why teams use them
- Better cell-cell and cell-matrix interactions than 2D
- More physiologically relevant phenotypes in many cases
Common limitations
- Heterogeneity between samples
- Limited control of gradients, transport, and mechanical cues unless engineered
2. Organoids (self-organizing biology)
Organoids are self-organizing cell cultures that can model aspects of native tissue architecture and function. The FDA roadmap describes organoids as miniature organ units (e.g., liver organoids, gut organoids) built from human cells.
Why teams use them
- Strong biological relevance for certain tissues
- Useful for disease modeling and patient-derived biology
Common limitations
- Variability between batches, sites, and time points
- Challenges with standardization and scalability
This is where reproducibility becomes a central theme. As Jos Joore puts it in the webinar: Biology is hard to repeat across sites and time points, and multi-site reproducibility is essential if NAMs are to move toward regulatory implementation.
3. MPS and organ-on-a-chip (engineered physiology)
MPS are often referred to as organs-on-chips. The FDA roadmap describes organ-on-a-chip devices as going beyond organoids by incorporating microfluidic flow, mechanical forces, and multi-cell type co-cultures on a bioengineered chip to emulate the in vivo environment.
In other words: MPS and organ-on-a-chip aim to combine human cells + engineered control (flow, forces, compartmentalization, and readouts) to produce more predictive biology.
Why teams use them
- Ability to model transport and perfusion (critical for many tissues)
- Multi-cell type co-cultures that better reflect tissue complexity
- Potential for more quantitative, functional endpoints
Common limitations
- Assay design still matters: without clear endpoints and context of use, complexity alone doesn’t help
- Standardization and validation are required for broader adoption
“Replacement” is not the first milestone—reproducible, fit-for-purpose assays are.
A recurring theme in both the FDA roadmap and the webinar is that adoption depends on rigor.
The FDA roadmap emphasizes that NAMs can enable “faster and more accurate human risk assessments,” but it also lays out the work needed to get there: mapping endpoints, validation pathways, reproducibility across labs, and qualification programs. In the webinar, Jos Joore frames it plainly: if we do not address reproducibility, endpoints, and assay design, NAMs can replicate the same issues we’ve seen with animal models.
A practical way to think about readiness is:
- Standardized biology (consistent starting material)
- Clear context of use (what decision the assay supports)
- Fit-for-purpose endpoints (what you measure and why)
- Clinical relevance (evidence that the signal maps to humans)
How to choose the right NAM model: a simple decision framework
When teams ask “Should we use organoids or organ-on-a-chip?”, the best answer is usually: it depends on the question. Here are four decision questions that can help you choose.
1. Do you need perfusion, transport, or gradients?
If your biology depends on flow (e.g., vascular effects, barrier integrity, immune cell trafficking, exposure dynamics), MPS/organ-on-a-chip approaches can be a better fit.
2. Do you need multi-cell type interactions and tissue interfaces?
If your mechanism depends on interactions between epithelium, stroma, vasculature, and immune components, look for systems that support co-culture without artificial barriers and allow functional readouts.
3. What endpoints will drive your decision?
Before selecting a model, define the endpoints that matter:
- Barrier integrity (e.g., TEER)
- Cytotoxicity and viability
- Cytokine release / immune activation
- Functional readouts (migration, electrophysiology, secretion)
Complexity is only useful if it produces quantifiable, decision-grade data.
4. What throughput is “fit for purpose”?
Throughput is not just for screening. Even a single compound tested across concentrations, replicates, and controls can quickly become dozens of data points. In the webinar, Jos Joore highlights that fit-for-purpose throughput is essential—a low-throughput complex model can be as limiting as a high-throughput simple model that lacks relevance.
Where organ-on-a-chip can add unique value
The FDA roadmap notes that microphysiological systems can be as predictive—or more predictive—than animal tests in certain contexts, and it points to examples like a Human Liver-Chip evaluated for drug-induced liver injury prediction and accepted into FDA’s ISTAND pilot program.
From a practical standpoint, organ-on-a-chip approaches are especially valuable when you need:
- Human-relevant biology under controlled exposure conditions
- Functional endpoints that map to clinical markers
- A path toward standardization and multi-site reproducibility
How MIMETAS approaches NAM readiness (OrganoPlate® differentiation)
At MIMETAS, the goal is to enable standardized, reproducible biology that supports fit-for-purpose assays today—and can progress toward broader adoption and regulatory implementation over time.
In the “What’s in a NAM?” webinar, Jos Joore describes a modeling philosophy that starts with human physiology and ends with decision-grade data:
- Comprehensive, human-relevant models that combine the cell types that matter (e.g., epithelium, stroma, vasculature, immune components)
- Functional, quantitative endpoints that translate into clear go/no-go insights
- Fit-for-purpose throughput so experiments can scale beyond a single condition and still stay practical
OrganoPlate®: engineered physiology with practical usability
The OrganoPlate® platform is built to bridge biological relevance and operational rigor. Key differentiators highlighted in the webinar include:
- Perfusion and flow in a microfluidic format, enabling controlled exposure and transport dynamics that are difficult to capture in static culture
- Membrane-free co-culture using PhaseGuide™ technology, allowing different cell types to interact without artificial barriers
- High-quality imaging enabled by microscope-grade glass (150 µm thin), supporting 3D microscopy and detailed phenotyping
- Fit-for-purpose throughput in a 384-well plate format, compatible with liquid handlers and automated workflows
- Low-absorbent materials to support more reliable compound testing
Quantitative endpoints and assay design
A model is only as useful as the data it produces. The webinar emphasizes building assays around measurable endpoints, including examples such as:
- Barrier integrity (e.g., TEER)
- Cytotoxicity and viability (e.g., LDH/ATP)
- Immune cell recruitment and migration under gradients
- Vascular inflammation readouts (e.g., PBMC adhesion under flow)
This focus on quantification is critical for moving from “interesting biology” to decision-grade evidence.
QA and reproducibility as the starting point
If NAMs are to support broader adoption, reproducibility has to be designed in. In the webinar, Jos Joore describes QA measures that safeguard microfluidic performance and reduce variability, and he shares examples of robust assay performance at scale (e.g., low coefficients of variation and strong assay quality metrics in large screens). This matters because reproducibility is not only a scientific requirement—it’s the foundation for multi-site studies, validation, and eventually regulated use cases.
What’s next: learn more and take action
If you’re exploring NAMs for the first time—or looking to strengthen your model strategy—start with two steps:
- Clarify your context of use: what decision will the data support?
- Choose endpoints first: then select the model that can deliver them reproducibly.
To go deeper into how organ-on-a-chip models and assays move from current applications toward regulatory implementation, watch the on-demand webinar recording.
Ready to take the next step?
If you want to evaluate whether an OrganoPlate®-based assay is fit for your context of use—barrier integrity, inflammation, immune recruitment, toxicity, or efficacy—reach out to the MIMETAS team to discuss the right model design, endpoints, and throughput for your program.