NAMs, NIH Policy, and What it Means for Diagnostics

The NIH’s growing emphasis on New Approach Methodologies (NAMs) marks a significant change in how biomedical research, particularly drug development, is being conducted. Prompted by legislative changes, evolving regulatory guidance, and long-standing concerns about the ethics and limits of animal models, NAMs are increasingly being used to study drug safety, pharmacology, and biological mechanisms using human-relevant systems such as organoids, microphysiological systems, advanced cell cultures, and computational models.

This shift has important implications for pharmaceutical R&D and regulatory science. For the diagnostics industry, the impact is more nuanced. NAMs are generally not diagnostic tools, and they are not designed to generate clinical diagnostic tests. Instead, their relevance to diagnostics lies mostly upstream, in how biological questions are framed and explored in research and translational phases, most often within drug development programs.

Focus on Replacing Animal Models in Drug Development

At a practical level, NAMs are mostly being adopted to replace or reduce animal testing in areas such as toxicology, pharmacokinetics, and target validation. For example, replacing an animal model with a liver-on-a-chip system can improve how researchers study drug-induced liver toxicity. That improvement matters for drug safety decisions, but it does not directly produce a new diagnostic test or change how existing diagnostics are developed or regulated.

Where NAMs May Influence Diagnostics

Although NAMs are often applied in drug development, they can still influence diagnostics indirectly by shaping the biological relevance of early research. More predictive preclinical models can help refine which molecular targets or pathways advance into later development, and which are deprioritized. In some cases, this upstream filtering can strengthen the scientific rationale for certain biomarkers that later become part of molecular assays or companion diagnostic (CDx) strategies.

Examples of overlap between the NAMs efforts and diagnostics R&D occur in four key areas:

1. Biomarker Discovery and Advanced Disease Modeling

To diagnose a disease early and accurately, scientists need to know exactly which biomarkers (specific proteins, genetic mutations, or metabolites) to look for. Traditional animal models often fail to express the same biomarkers as humans. By using advanced in vitro patient-derived organoids and organs-on-a-chip, researchers can better replicate human disease states in the lab to identify novel biomarkers. For instance, in March 2026, Johns Hopkins researchers received a $15 million Complement-ARIE grant to develop the DROIDp platform, which uses brain organoids and advanced analytics to model neurological diseases such as Alzheimer’s. The system is designed to provide a more human-relevant way to study neural function, including learning and memory, and to improve drug and toxicity testing.

2. “Clinical Trials on a Chip” and Companion Diagnostics

The line between a drug screening tool and a diagnostic tool becomes arguably fuzzier when dealing with personalized medicine. NYU Langone Health and Sage Bionetworks won a $25 million NIH grant to create the NYU‑Sage NAMs Data Hub, centralizing and standardizing data from advanced human-based models like organoids and organ-on-a-chip systems. The hub will accelerate research, enable AI-powered insights, and make these cutting-edge methods interoperable and widely accessible across the scientific community

By testing therapies like CAR T-cells on the patient’s chip, doctors can predict the tumor’s response and potential toxicities before treating the actual human. In this way, the NAM acts as a type of advanced companion diagnostic, or more precisely, a test used to determine whether a specific patient is suitable for a particular treatment.

3. Biosensor Hardware and Miniaturization

To make organs-on-a-chip work, in some cases engineers have to integrate highly sensitive, miniaturized biosensors directly into the microfluidic channels to monitor characteristics of cellular health, oxygen levels, and metabolic byproducts in real time. The R&D required to make these sensors overlaps significantly with the technologies driving many of the next generation of point-of-care (POC) diagnostics. Advancements made in integrating biosensors into microfluidic platforms allow for rapid, low-cost, often parallelized tests with reduced reagent use, which directly feeds into the development of various other products such as wearable health monitors and rapid bedside diagnostic tests.

4. AI and High-Dimension Data

Advanced NAMs and some of the newer diagnostics can rely heavily on complex, high-dimensional data streams. The in silico AI models being developed to interpret the massive amounts of multi-omics and biosensor data generated in research are often applicable or transferable to diagnostics. Whether an AI is trained to recognize a toxic reaction in a liver-on-a-chip or trained to recognize a disease signature from a patient’s blood sample, the underlying machine learning algorithms and data processing challenges are remarkably similar.  Progress in these areas will benefit the related applications in diagnostics.

Broader Long-Term Effects

Ultimately, building a synthetic system that accurately mimics aspects of human biology to test a drug requires multiple advances in engineering, biological understanding, and analytical tools which in a broad sense will also contribute to the technologies used to diagnose human disease.  By improving early target validation and reducing attrition in drug development, NAMs may indirectly support more stable drug–diagnostic co-development strategies as well. This matters especially because companion diagnostics remain one of the most strategically important segments of the diagnostics market. Kalorama’s research consistently shows that oncology-focused companion diagnostics represent the majority of CDx revenues, reflecting the shift toward targeted therapies and precision medicine.

Learn More from Kalorama Information

Kalorama Information continues to track diagnostic segments that directly or indirectly intersect with the scientific and market dynamics discussed here. Our coverage includes World Market for Molecular Diagnostics, 14th Edition, Companion Diagnostics (CDx) Markets: Global Trends, Opportunities, and Forecasts, 4th Edition, and The Worldwide Market for Liquid Biopsy, 7th Edition, among an extensive catalog of market research reports.

Visit our website to explore these reports and gain deeper insight into how evolving research approaches are shaping diagnostic markets.