Flow Cytometry: A Tool for New Approach Methodologies

Flow cytometry rapidly analyzes thousands of lined up suspension cells, making it ideal for high-throughput applications. Its multiparametric capability can support alternatives to traditional animal testing. 

Flow cytometric methods are relevant throughout drug development, spanning basic research, translational medicine and clinical diagnostics. This bridging role is expanding, driven by technological innovations with consistent market growth for flow cytometry platforms and rising demand for high-resolution, single-cell quantification.¹ Adding immune status information, such datasets are increasingly combined with genomics, transcriptomics, and proteomics to refine a systemic view of cell biology and functionality, disease mechanisms and drug response.² As the technology evolves with spectral flow and mass cytometry, it can further integrate into the New Approach Methodology (NAM) framework aimed at replacing or reducing research animal use.

NAMs aim to uncover mechanisms of toxicity in reliable in vitro alternatives. Since the FDA announcement in April 2025 on phasing out animal testing requirements, a new NIH initiative supports this paradigm shift. Flow cytometry enables detailed analysis of cellular responses in human cell lines or primary cells. The support of tiered testing strategies, for example, comes through high-throughput insights into cytotoxicity (e.g. viability, apoptosis, necrosis) or monitoring of intracellular signaling pathways, oxidative stress, and cell cycle alterations, helping to speed up regulatory screening.

By detecting micronuclei MicroFlow® and MultiFlow® assays, for example, you can assess multiple genotoxicity endpoints simultaneously. These assays can be combined with the TGx-DDI transcriptomic biomarker to effectively evaluate data-poor compounds.³ Another highly sensitive method is the PIG-A assay⁴ that requires only microliter volumes of peripheral blood, making it suitable for genotoxicity screening without additional animal use. This assay detects somatic mutations by identifying cells lacking GPI-anchored surface proteins, such as CD24 or CD59. This has been adopted by the FDA for evaluating pharmaceuticals and industrial chemicals.

When combined with 2D/3D cultures or organoids, dissociated cells can be phenotyped for identifying cell-type specific markers and potential stress responses without relying on animal models. By linking molecular events to toxic outcomes flow cytometry can help in developing adverse outcome pathways (AOPs). Its methods are customizeable for evaluating immune cell responses (cytokine production, activation markers), supporting NAMs in immunotoxicology and inflammation studies. For example, to study the mechanisms of action of anti-TNF therapies such adalimumab, etanercept, or infliximab and to capture donor heterogeneity, a novel functional assay was developed.⁵ It involves LPS whole blood stimulation and subsequent analysis of surface marker expression changes of primarily CD69, CD16, and transmembrane TNF, providing insights into immune responses and therapeutic efficacy.

Regulatory frameworks like OECD increasingly accept flow cytometric measurements, such as the h-CLAT assay. It identifies skin sensitizers by detecting CD54 and CD86 upregulation on THP-1 human monocytes. This in vitro method has been integrated into Test Guideline 442E. It is widely used to address skin sensitization after 24 hour chemical exposure and has been adapted to include assessment of inorganic nanomaterials.⁶

These examples illustrate how flow cytometry is already applied for NAMs, ranging from regulatory testing to advanced computational analysis, all aimed at reducing reliance on animal models, while enhancing the efficiency of toxicological assessments. Real-time, multiparameter analysis of individual cells remains important for understanding cellular heterogeneity in tumors, the immune system, and developmental biology. Flow cytometric data complexity and standardization remain hurdles, but efforts like the Human Cell Atlas, MIFlowCyt criteria and the SOULCAP initiative are driving global immune ontology and data harmonization.

AI, digital twin technology and imaging data integration combined with multi-omics approaches⁷ will expand flow cytometry applications in drug development and biomedical research, helping to develop NAMs across various domains, including genetic toxicology, immunology, and functional genomics.

References:
1.    Robinson JP, Ostafe R, Iyengar SN, et al. Flow Cytometry: The next revolution. Cells, 2023, 12:1875. doi: 10.3390/cells12141875
2.    Wang X, Fan D, Yang Y, et al. Integrative multi-omics approaches to explore immune cell functions: Challenges and opportunities. iScience, 2023, 26:106359. doi: 10.1016/j.isci.2023.106359
3.    Fortin A-MV, Long AS, Williams A, et al. Application of a new approach methodology (NAM)-based strategy for genotoxicity assessment of data-poor compounds. Front. Toxicol., 2023, 5:1098432. doi: 10.3389/ftox.2023.1098432
4.    Araten DJ, Nafa K, Pakdeesuwan K, Luzzatto L. Clonal populations of hematopoietic cells with paroxysmal nocturnal hemoglobinuria genotype and phenotype are present in normal individuals. Proc Natl Acad Sci USA, 1999, 96:5209-5214. doi: 10.1073/pnas.96.9.5209
5.    Garcia CC, Lefevre A, Busnel J-MR. Development of a flow cytometry-based functional assay to study anti-TNF mechanisms of action and capture donor heterogeneity. Immunohorizons, 2020, 4:648-658. doi: 10.4049/immunohorizons.2000077
6.    Wareing B, Hippchen AA, Kolle SN, et al. Limitations and modifications of skin sensitization NAMs for testing inorganic nanomaterials. Toxics., 2024, 12:616. doi: 10.3390/toxics12080616
7.    Acosta JN, Falcone GJ, Rajpurkar P, Topol EJ. Multimodal biomedical AI. Nat Med., 2022, 28:1773-1784. doi: 10.1038/s41591-022-01981-2