Omics in Short-Term Toxicology Studies: Are We Ready to Replace Traditional Approaches? 

Toxicology is at a turning point. For decades, decision-making relied on long-term animal studies, which included 90-day or even 2-year rodent trials, to identify adverse effects, set exposure limits, and protect human health. But these studies are costly, slow, and increasingly misaligned with today’s push for human-relevant, mechanism-based safety evaluations that minimize animal use and maximize compound success. 

A recent commentary from the Society of Toxicology 2025 session “Navigating Complexity in Modern Toxicology: The Role of Omics in Short-Term In Vivo Studies” by Mitchell et al., 2025 lays out how short-term in vivo studies that are enhanced with omics technologies, like transcriptomics, metabolomics, and proteomics, could become a powerful bridge between traditional animal testing and next-generation risk assessment (NGRA) (1). 

For toxicologists in the pharmaceutical, industrial chemical, agrochemical, and cosmetics sectors, the critical question is: can short-term studies that embrace omics deliver the mechanistic depth, reproducibility, and regulatory acceptance needed to make them viable alternatives to current practice? 

From Long-Term Pathology to Early Molecular Indicators with Omics 

Traditionally, toxicology has relied on subchronic (months-long) and chronic (years-long) in vivo studies to estimate effect levels, identify target organ toxicity, and derive relevant reference values that inform outcomes (2). These studies often focus on apical endpoints like liver hypertrophy, tumors, or developmental defects. However, this approach is resource-intensive, time-consuming, and doesn’t align with the push for human-relevant, high-throughput studies that reduce animal usage while maximizing post-exposure insights.  

By contrast, omics approaches such as transcriptomics, metabolomics, proteomics, epigenomics, and high-throughput image-based approaches like Cell Painting, can detect molecular changes in short-term in vivo studies within 5–28 days of exposure, long before pathology emerges (3-5). This ultimately enhances the speed, sensitivity, and resolution of toxicity testing while increasing human relevance and reducing or refining the reliance on animal studies (1).  

Crucially, toxicologists can use these omics-based insights to derive early, mechanistic markers as the starting point for estimating safe exposure levels, known as molecular ‘points of departure (POD)’ to provide a more efficient, mechanistically informed approach to chemical safety evaluation (6,7). Traditionally, PODs are derived from animal studies based on apical endpoints such as organ weight changes or pathology. Molecular PODs extend this concept upstream, defining a threshold based on transcriptomic or pathway-level perturbations that precede overt toxicity. 

Molecular PODs might include: 

• Gene expression alterations (transcriptomics) 

• Protein or pathway changes (proteomics, signaling biomarkers) 

• Epigenetic or metabolic signatures (methylation, metabolomics) 

By capturing shifts in gene expression, protein abundance, or metabolic pathways, omics-enhanced short-term toxicology studies can: 

• Provide early biomarkers of toxicity (7) 

• Enable molecular points of departure (mPODs) that precede traditional outcomes (4) 

• Support potency ranking and hazard identification (1) 

• Drastically reduce study timelines, animal usage, and costs (1) 

An Omics-based Molecular Point of Departure Case Study 

The specific safety data requirements for toxicological assessments vary across sectors, ranging from the comprehensive preclinical and clinical testing required in pharmaceuticals to the alternative methods used in cosmetics due to the prohibition on animal testing. 

While each industry may require different data, guidelines for the use of molecular PODs are already here and provide a helpful starting point for other areas. For example, the U.S. Environmental Protection Agency’s Transcriptomic Assessment Product (ETAP) program uses targeted RNA-seq in five-day repeated oral dose rat studies to derive transcriptomic points of departure (tPODs) (6,8).  

These tPODs are determined from the detection of consistent changes across gene expression pathways or biological processes from the lowest median benchmark dose at the lower 95% confidence limit. By performing RNA-seq on a series of potential target organs, toxicologists can derive transcriptomic reference values for health assessments, thereby reducing the experimental turnaround time from years to months. 

For instance, this ETAP approach rapidly established a reference value for a data-poor PFAS compound, perfluoro-3-methoxypropanoic acid (MOPA), which would have required significant investment and years to obtain through conventional studies (9). 

Objection #1: “How Do We Know Omics Data Are Reliable?” 

Concern: Many toxicologists worry about variability in RNA-seq pipelines, from normalization to benchmark dose (BMD) modeling. Different workflows could mean different answers. 

Response from the field: While transcriptomics provides unprecedented scientific value, its regulatory application depends on consistent, reproducible bioinformatics pipelines for data processing, analysis, and interpretation. Collaborative efforts, including Health and Environmental Sciences Institute (HESI)-led multi-sector groups, are tackling this head-on and aim to harmonize bioinformatics pipelines.  

Computational tools, such as BMDExpress v3.0, now integrate ToxicR-based modeling to better retain biologically plausible dose–response relationships, thereby improving the reliability of BMD derivation (10). The Regulatory Omics Data Analysis Framework (R-ODAF) also goes some way toward standardizing the selection of differentially expressed genes for toxicological applications, filtering non-biologically relevant signals, and providing robust pathway-level interpretation (11). Transparent bioinformatics pipelines are now being validated against traditional endpoints to build regulatory confidence. 

Objection #2: “Regulators Won’t Accept Omics Data Yet.” 

Concern: Why invest in omics if agencies still demand apical outcomes? 

Response: Regulatory bodies are already exploring omics integration. The U.S. EPA, the Organisation for Economic Co-operation and Development (OECD), and the European Centre for Ecotoxicology and Toxicology of Chemicals (ECETOC) are developing best practices for transcriptomic data in risk assessment. Omics-based studies are already aligned with traditional outcomes. For instance, in developmental and reproductive toxicity studies, omics-derived PODs have fallen within 2–3x of apical values, showing strong concordance (12). Similarly, the ECETOC Smart Studies Task Force reported that the majority of adverse findings in 90-day studies were detectable at 28 days in a retrospective analysis of 113 chemical pairs with data for both timepoints (13). Regulators clearly recognize the potential for omics to fill data gaps for data-poor chemicals, particularly under frameworks like the Toxic Substances Control Act (TSCA). 

Objection #3: “Short-Term Studies Might Miss Long-Term Effects.” 

Concern: Can 5–28-day studies really capture what 90-day or 2-year studies reveal? 

Response: As mentioned, retrospective analyses show that most adverse findings in 90-day studies are already detectable at 28 days (13). For endpoints sometimes missed, like subtle liver or hematology effects, omics provides added sensitivity. By layering transcriptomics or metabolomics into standard OECD 28-day designs, toxicologists can both detect early effects and de-risk chemicals with greater confidence. Taking a multiomics approach can provide even greater sensitivity at multiple layers of the molecular phenotype. Combining these approaches with traditional approaches would cover all bases and make for all-around smarter decision-making. 

Expanding Beyond Traditional Transcriptomics with Alithea Genomics 

While transcriptomics is the most mature omics tool, traditional RNA-seq methods aren’t sufficiently scalable and remain expensive for large-scale studies. Similarly, more cost-effective targeted approaches miss the majority of genes available, which might mean important signals aren’t detected. Thus, the field is rapidly moving toward scalable, ultra-high-throughput, automatable RNA-seq approaches, like DRUG-seq, BRB-seq, and their derivatives (14,15).  

Alithea Genomics provides toxicologists with a suite of robust, high-throughput, and cost-effective RNA-seq technologies that improve upon the original DRUG-seq and BRB-seq protocols with optimization for direct assessment of purified RNA, whole cells, blood, spheroids, FFPE samples, and ultra-low input amounts, maximizing the value of precious samples. 3’ and full-length options provide toxicologists with robust transcriptome-wide gene expression data, including the capture of both coding and non-coding transcripts.   

Multi-omics integration adds even more clarity to toxicology studies. Blood-based transcriptomics, metabolomics, and proteomics offer minimally invasive endpoints, while tissue-based omics provide deeper mechanistic insights. Together, these datasets improve confidence in hazard characterization and reduce the need for large animal cohorts. 

Why This Matters for Toxicology Studies 

For decision-makers, the question is no longer “if” omics will be part of toxicology, but “when and how”. 

Key benefits of adopting omics-enabled short-term studies: 

• Faster, mechanism-based decision-making 

• Reduced costs compared to chronic animal studies 

• Early alignment with evolving regulatory expectations 

• Stronger scientific credibility in explaining modes of action 

• Competitive advantage in meeting demands for human-relevant, animal-reduced toxicology 

As with any integration of novel technology and the associated regulatory changes, challenges remain: harmonization of bioinformatics pipelines, laboratory training, and global regulatory alignment. But as Mitchell et al. (2025) conclude, the field is moving beyond theory. Omics-enabled short-term studies are already shaping the future of chemical safety assessment. 

Final Takeaway 

If your company is still relying solely on traditional long-term rodent studies with or without integrating omics endpoints, you may be investing time and money into approaches that are slower and less informative. By embedding omics technologies into short-term studies, it is now possible to predict toxicity faster, gain deeper mechanistic insights, and generate data that regulators are beginning to accept. 

For companies conducting toxicology studies, the opportunity is clear: consider integrating omics or risk being left behind as the industry shifts toward next-generation, mechanism-driven risk assessment. 

Feel free to contact us to learn more about how high-throughput transcriptomics can improve your next toxicology study in the era of next-generation risk assessment to save you time and money while boosting human relevance.   

References 

1. Mitchell CA, Wehmas L, Rouquie D, Caiment F, Currie RA, Crute CE. Navigating Complexity in Modern Toxicology: The Role of Omics in Short-Term In Vivo Studies. Toxicological Sciences. 2025 Aug 25:kfaf120. 
2. Schmeisser S, Miccoli A, Von Bergen M, Berggren E, Braeuning A, Busch W, Desaintes C, Gourmelon A, Grafström R, Harrill J, Hartung T. New approach methodologies in human regulatory toxicology–Not if, but how and when!. Environment international. 2023 Aug 1;178:108082. 
3. Joseph P. Transcriptomics in toxicology. Food and Chemical Toxicology. 2017 Nov 1;109:650-62. 
4. Johnson KJ, Auerbach SS, Stevens T, Barton-Maclaren TS, Costa E, Currie RA, Dalmas Wilk D, Haq S, Rager JE, Reardon AJ, Wehmas L. A transformative vision for an omics-based regulatory chemical testing paradigm. Toxicological Sciences. 2022 Dec 1;190(2):127-32. 
5. Yuan K, Nault R. Application of a metabolic network-based graph neural network for the identification of toxicant-induced perturbations. Toxicological Sciences. 2025 Jul;206(1):19-29. 
6. EPA. (2024b). Scientific Studies Supporting Development of Transcriptomic Points of Departure for EPA Transcriptomic Assessment Products (ETAPs). https://epa.figshare.com/articles/online_resource/Scientific_Studies_Supporting_Development_of_Transcriptomic_Points_of_Departure_for_EPA_Transcriptomic_Assessment_Products_ETAPs_/25365550 
7. Corton JC, Mitchell CA, Auerbach S, Bushel P, Ellinger-Ziegelbauer H, Escobar PA, Froetschl R, Harrill AH, Johnson K, Klaunig JE, Pandiri AR. A collaborative initiative to establish genomic biomarkers for assessing tumorigenic potential to reduce reliance on conventional rodent carcinogenicity studies. Toxicological Sciences. 2022 Jul 1;188(1):4-16. 
8. EPA. (2024c). Standard Methods for Development of EPA Transcriptomic Assessment Products (ETAPs). https://epa.figshare.com/articles/online_resource/Standard_Methods_for_Develo 
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10. EPA. (2024a). EPA Transcriptomic Assessment Product (ETAP) for Perfluoro-3-Methoxypropanoic Acid. 
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13. Waterbury CR, Crockett MN, Conley JM, Lambright CS, Wehmas LC. Targeted RNA-sequencing of testes from fetal rats exposed to dicyclohexyl phthalate informs potency and adverse outcome pathway development. Toxicological Sciences. 2025 Jul 21:kfaf106. 
14. Escher SE, van Ravenzwaay B, Schmitt B. Toxicological effects in 28-day studies compared to 90-day studies–what do we miss after short term exposure?. Arhiv Za Higijenu Rada i Toksikologiju. 2024;75:72-. 
15. Ye C, Ho DJ, Neri M, Yang C, Kulkarni T, Randhawa R, Henault M, Mostacci N, Farmer P, Renner S, Ihry R. DRUG-seq for miniaturized high-throughput transcriptome profiling in drug discovery. Nature communications. 2018 Oct 17;9(1):4307. 
16. Alpern D, Gardeux V, Russeil J, Mangeat B, Meireles-Filho AC, Breysse R, Hacker D, Deplancke B. BRB-seq: ultra-affordable high-throughput transcriptomics enabled by bulk RNA barcoding and sequencing. Genome biology. 2019 Apr 19;20(1):71.