Breaking Through the Barriers to NAMs Adoption

New Approach Methodologies (NAMs) are poised to transform preclinical research and toxicology. We recently talked about three interconnected barriers to in vitro NAMs adoption: cell sourcing, standardization and regulatory acceptance. While the barriers are real, progress is being made on all three fronts. Moving NAMs into the mainstream will require approaches that tackle all three together.

The Path to NAMs Adoption

The path from promising science to mainstream practice has always required more than good technology. It requires the field to build shared infrastructure—biological standards, common protocols, submission-grade evidence—that no single organization can create alone.

Strengthening Biological Foundations

While gaps exist for both in vitro and in silico models, today we’re focusing on in vitro models. The credibility of any NAM study starts with the biological system generating the data. That means moving away from using whatever cells are available and toward deliberate, well-characterized selection based on the specific goals of a given study.

In practice, that requires progress on several fronts:

• Cell source selection and characterization: Primary human cells, iPSC-derived cells and immortalized cell lines each have tradeoffs in relevance, consistency and maturity. Choosing the right source for a given application, and documenting that choice transparently, are foundational to defensible data.
• Donor diversity. Most NAM studies still rely on cells from a single donor. But drug responses vary across age, sex and genetic background, and models need to reflect that if they're going to predict how therapies behave across real patient populations. iPSC banks, which offer renewable and genetically diverse cell lines, are making this more achievable.
• Honest assessment of technical maturity. Some cell types are ready for regulated use; others aren't there yet.Knowing the difference and being transparent about the limits of a given model is what makes data trustworthy.

Building Shared Standards

Even well-designed studies lose their value if results can't be compared across laboratories or programs. Standardization doesn't mean every lab runs identical protocols, but it does mean having enough common ground that data generated in one program can contribute to collective knowledge rather than sitting in isolation.That will require:

• Cross-laboratory comparison studies and ring trials that test whether different labs running the same methods get comparable results and reveal where protocols need to converge.
• Shared reference datasets that give the field a common baseline for understanding normal variability and expected performance across different model types.
• Clearer, more operational definitions of "fit for purpose," specific enough to guide method selection and distinguish the evidentiary bar for a screening assay from that of a pivotal safety study.

Generating Regulatory-Ready Evidence

Regulatory confidence isn't granted. It's earned through cumulative, well-documented evidence. For NAMs data to support real decisions, it needs to be generated with the rigor those decisions require:

• Documented quality controls, traceable methods and SOPs built for regulatory use from the start, not retrofitted after the fact.
• Benchmarking against human clinical outcomes where that data exists, not just against in vivo results. Where NAMs studies diverge from data generated byestablishedin vivomodels,it’simportant to remember that divergence may reflect greater human relevance, not a model failure.
• Transparent reporting of both performance and limitations, including failures. Selective reporting of favorable results undermines the credibility the field is working to build.

The infrastructure around a study (documentation, quality systems, traceability) is less visible than the science itself, but it's what makes data defensible when it counts.

Putting NAMs into Practice

The barriers to NAMs adoption are real, but they aren't insurmountable. What the field needs now is organizations willing to do the unglamorous work: rigorous cell characterization, disciplined study design and quality systems built for regulatory use.

At Battelle, this is where we focus. We bring a platform-agnostic perspective toNAMsdevelopment, selecting cell sources and model systems based on scientific fit rather than convenience or proprietary commitment, and generating data within a regulatory-ready quality framework. Our work spans the full range of disciplines that serious NAM studies require: cell biology, analytical chemistry, engineering and quality systems. And because we've spent years navigating drug development tool qualification processes, we understand what it takes to generate evidence that holds up under scrutiny.

The organizations best positioned when the regulatory landscape fully catches up to the science will be those that started building that foundation early. We'd welcome the conversation about where NAMs fit in your development strategy and what it would take to get there.