In Vitro Cell Models in Toxicology

The problem with traditional toxicology models

Animal models have been the backbone of toxicology for decades. Researchers frequently use rodents, dogs, and non-human primates to test the safety of chemicals, pharmaceuticals, and environmental toxins.¹ While these models offer whole-organism context, they come with significant drawbacks.^2,3

Limitations of traditional toxicology models:

• Species differences – Animal responses often fail to predict human toxicity accurately.

• Ethical constraints – Public and regulatory pressure to reduce animal testing is increasing

• High costs and long timelines – Preclinical animal studies can take months to years and cost millions.

• Limited throughput – Screening large compound libraries is impractical using in vivo models alone.

Researchers and regulators are looking for smarter, faster, and more human-relevant solutions. That’s where in vitro models come into the picture. 

Why in vitro models make sense

In vitro cell models—cultures of cells grown outside their natural environment, from 2-D monolayers to complex 3-D organoids—offer a more controlled and scalable approach to toxicity testing.⁴ These systems range from simple monolayers of immortalized cell lines to complex 3-D organoids and microphysiological systems (“organ-on-chip”).⁵

Here’s what makes them so compelling:

• Controlled environment - Precise experimental conditions can be maintained.

• Human relevance – Human cells or tissues can be used.

• High throughput – Large numbers of compounds can be screened.

• Reduced costs – lower expenses as compared to animal testing.

While these benefits have prompted growing investment and regulatory interest in alternative testing strategies, the road ahead is not without challenges.

Current limitations and skepticism

Despite their potential, in vitro models are not a panacea. Several limitations currently hinder their widespread adoption:^6-8

• Physiological complexity – In vitro systems often lack the dynamic environment of living organisms.

• Data interpretation – Translating in vitro endpoints to in vivo outcomes in complex.

• Variability and standardization – Reproducibility is an issue, especially for primary cells and organoids.

• Regulatory hesitancy – Regulatory agencies still rely heavily on animal data for safety decisions.

Rather than asking whether in vitro models can replace animal testing entirely, a more productive question might be “how can these tools best complement existing methods?”

How ATCC’s innovative solution pushes the field forward: Bridging the genotype-phenotype gap

One of the biggest challenges with in vitro toxicology is knowing how reliable your cell models really are. Are they what they claim to be? Do they reflect the biology you’re trying to study? Are you getting data you can trust? 

That’s where ATCC is stepping in with a unique solution. As a global leader in biological materials, ATCC is not only providing rigorously authenticated human and animal cell models but also building robust omics reference databases through next-generation sequencing (NGS) technologies.⁹

ATCC’s approach for linking genotype to phenotype

• Authenticated, traceable cell models – Every model undergoes rigorous verification to confirm identity and purity.

• Omics reference databases – Using NGS, ATCC generates detailed omics profiles—whole exomes, transcriptomes, and more— for each model.

This enables researchers to select models that match the biology and toxicological pathways they intend to study, improving experimental design and predictive power. ATCC’s approach transforms cell lines from mere experimental tools into data-rich platforms for informed decision making.

Put simply, ATCC isn’t just offering cell lines—we’re building data-driven platforms for decision-making. That’s a game-changer for toxicology workflows.

The real future? Integration—in vitro and in silico approaches, not replacement

The most exciting developments in toxicology aren’t about pitting in vitro against in vivo—it’s about combining the best of all worlds.^4,10 Integrating high-quality in vitro data with computational modeling (think QAT, PBPK, and machine learning) is already unlocking more predictive and scalable toxicology approaches.^4, It’s a shift from asking, “can this compound cause harm?” to “what’s the mechanism, the dose, and the human risk?” That’s where toxicology needs to go, and where many in the field are already heading.

When combined, these technologies can:

• Improve predictive accuracy
• Enable more robust dose extrapolations
• Reduce reliance on animal studies while maintaining safety standards

This hybrid model of toxicology R&D—blending in vitro, in silico, and in vivo data—could accelerate innovation while addressing scientific, ethical, and regulatory concerns.

Final thoughts: Building smarter toxicology from the ground up

In vitro models aren’t a silver bullet—but they are reshaping how we think about toxicology. They’re faster, more human-relevant, and with the right backing—like ATCC’s authenticated, omics-informed cell models—they can be much more powerful.

We must take the next step to use these tools thoughtfully and in the right context. That means continuing to validate, share data, and build bridges between experimental science and regulatory science.

This matters because ultimately, better models lead to better decisions—and better outcomes for patients, consumers, and the environment. To learn more about the cell models backed with omics data, visit the ATCC Genome Portal. 

Did you know?

The ATCC Genome Portal has data from over 900 unique authenticated cell lines from ATCC's biorepository.

Learn more about the ATCC Genome Portal

References

1. Vashishat A, et al. Alternatives of Animal Models for Biomedical Research: a Comprehensive Review of Modern Approaches. Stem Cell Rev Rep 20(4): 881–899, 2024. PubMed: 38429620
2. Hartung T. The (misleading) role of animal models in drug development. Front Drug Discov 4: 1355044, 2024.
3. Van Norman GA. Limitations of Animal Studies for Predicting Toxicity in Clinical Trials: Is it Time to Rethink Our Current Approach? JACC Basic Transl Sci 4(7): 845–854, 2019. PubMed: 31998852
4. Singh AP, et al. Enteroendocrine Progenitor Cell-Enriched miR-7 Regulates Intestinal Epithelial Proliferation in an Xiap-Dependent Manner. Cell Mol Gastroenterol Hepatol 9(3): 447–464, 2020. PubMed: 31756561
5. Madorran E, et al. In vitro toxicity model: Upgrades to bridge the gap between preclinical and clinical research. Bosn J Basic Med Sci 20(2): 157-168, 2020. PubMed: 31621554
6. Ghallab A,  Bolt HM. In vitro systems: current limitations and future perspectives. Arch Toxicol 88(12): 2085–2087, 2014. PubMed: 25370013
7. Ge J-Y, et al. Trends and challenges in organoid modeling and expansion with pluripotent stem cells and somatic tissue. PeerJ 12: e18422, 2024. PubMed: 39619184
8. Fuhr A, et al. Organoids as Miniature Twins—Challenges for Comparability and Need for Data Standardization and Access. Organoids 1: 28–36, 2022.
9. Singh AP, et al. Genomic Discovery of EF-24 Targets Unveils Antitumorigenic Mechanisms in Leukemia Cells.PLoS One 20(9): e0330906. PubMed: 40986633
10. Pognan F, et al. The evolving role of investigative toxicology in the pharmaceutical industry. Nat Rev Drug Discov 22(4): 317–335, 2023. PubMed: 36781957