As the SOT Annual Meeting and ToxExpo 2026 approaches, we take a pre-conference look at the programme through a transcriptomics-focused lens. One overall shift is clear: toxicology is moving from descriptive apical observation toward predictive, mechanism-driven safety science. Across the programme, many sessions highlight how transcriptomics and other omics technologies are enabling toxicologists to generate mechanistic insight at scale, prioritize chemicals earlier in development, derive transcriptional points of departure for better safety assessment, and predict systems-level toxicity using human-relevant models and AI.
Read on for the three primary themes to watch out for and some hand-picked ‘don’t miss’ sessions at the SOT Annual Meeting and ToxExpo 2026.
Attending the SOT Annual Meeting and ToxExpo 2026? Come to our exhibitor session on Tuesday, March 24th, from 1:45 PM to 2:45 PM, Room 24a, or visit us at ToxExpo booth #807
Alithea’s Co-founder, Daniel Alpern, and Sales Executive Andrea Hadjikyriacou will demonstrate how screening-scale transcriptomics, powered by DRUG-seq, can complement Cell Painting high-content imaging by linking transcriptional signatures to rich morphological phenotypes for next-generation risk assessment (NGRA). They will show how this combination strengthens mechanistic interpretation, improves confidence in biological pathway mapping, enhances compound clustering, and boosts MoA prediction for AI-driven toxicology.
We’re also excited to host two industry leaders in NGRA. Richard Currie, Syngenta Senior Fellow, will share real-world industrial experience applying DRUG-seq alongside complementary phenomics and metabolomics technologies to support NGRA decision-making, and Fred Ward from Axiom Bio will present Axiom’s experience integrating imaging, proteomics, and transcriptomics endpoints.
Explore outcomes from SOT 2025 in our discussion of the role of omics in short-term in vivo studies blog post.
SOT 2026 Theme 1: The Shift from Animal Studies First to NAMs + Omics First
One of the clearest trends at SOT 2026 is the shift from traditional animal-first testing strategies toward new approach methodologies (NAMs) paired with high-content omics readouts. Animal models often fail to capture human-specific responses to pharmaceuticals, chemicals, environmental agents, and biologics, potentially leading to missed late-stage toxicity, stalled pipelines, and risks to human health.
Integrating NAMs with high-throughput omics profiling now enables toxicologists to predict and detect pathway-level perturbations earlier and in more human-relevant systems, such as immune-competent 3D organoids and spheroids.
One Symposium session focuses on early-stage de-risking and compound selection through human-centered immunotoxicology assays paired with omics, to reduce the need for animal studies and support regulatory packages.
A Roundtable session then discusses whether mechanistic in vivo studies paired with transcriptomics could enhance predictive power and generate transcriptomic points of departure (tPODs) that capture concerted pathway-level changes rather than apical endpoints. These tPODs may be both more human-protective and more efficient than endpoints measured weeks or months later in conventional study designs, while reducing and refining animal use in developmental and reproductive toxicity (DART).
Recommended Sessions at SOT:
- Symposium Session: Rebuilding Immunity in the Lab: Complex In Vitro Models for Smarter Safety Science. Chairs: Mark Collinge, Pfizer Inc.; Chrissy Crute, HESI.
Monday, 23rd March, 2:00 PM to 4:45 PM, Ballroom 6E, Convention Center.
- Roundtable Session: Toward a New Paradigm: Can Mechanistic In Vivo Studies Replace Traditional DART Guideline Studies? Chairs: Shermaine Mitchell-Ryan, HESI; Leah Wehmas, US EPA.
Tuesday, March 24th, 4:30 PM to 6:00 PM, Room 1B, Convention Center.
SOT 2026 Theme 2: Transcriptomics on the Road to Regulatory Acceptance
Gene expression profiling has evolved well beyond its original role as a tool for mechanism identification. Several sessions make the case that transcriptomics is now ready to function as a quantitative decision tool. One that can deliver both a regulatory number and a mechanistic explanation for it simultaneously.
One strategically important Roundtable session discusses exactly this and frames the transcriptomics regulatory landscape with a question: Do we need a quantitative point of departure, a mechanistic pathway signature, or both? This captures the debate currently playing out between industry, academia, and regulators.
Gene expression profiling now provides health-protective PODs for provisional risk assessments, with validated biomarkers for genotoxicity, liver injury, and endocrine disruption already largely established. The session will explore beyond these established applications and will discuss how the integration of transcriptomics with other multidimensional datasets now meets the long-standing need for “phenotypic anchoring.” It will also highlight practical applications of toxicogenomic data in regulatory science, review emerging transcriptomic methodologies, and discuss strategies to make these data more interpretable and actionable for decision-makers.
Similarly, a Continuing Education session will discuss the integration and application of omics in the context of adverse outcome pathways (AOPs). AOPs provide convenient constructs for assembling and evaluating mechanistic information at different biological levels to support regulatory applications and are crucial for regulatory acceptance of new products.
A Symposium session then also addresses critical questions in immunotoxicology about translational relevance, regulatory uptake, and model standardization for NAMs + omics. It will discuss regulatory frameworks that are beginning to incorporate or accept NAM-based data and aims to offer toxicologists, immunologists, and risk assessors a ‘forward-looking view of how NAMs are redefining the landscape of immuno-safety across academia, industry, and government’.
Read our OASIS Consortium article about the development of an NGRA framework that harnesses high-content, human-relevant, and data-rich technologies, such as Cell Painting, high-throughput transcriptomics, and proteomics, to aid toxicologists and regulators.
Recommended Sessions at SOT:
- Continuing Education Course AM06: Systematic Methods for AOP Development and Application: New Technologies and Tools. Chairs: Bette Meek, University of Ottawa; Alexandra Schaffert, Tampere University.
Sunday, March 22nd, 8:15 AM to 12:00 Noon, Ballroom 6C, Convention Center - Symposium Session: Rebuilding Immunity in the Lab: Complex In Vitro Models for Smarter Safety Science. Chairs: Mark Collinge, Pfizer inc.; Chrissy Crute, HESI.
Monday, 23rd March, 2:00 PM to 4:45 PM, Ballroom 6E, Convention Center. - Roundtable Session: Do We Need a Number, a Pathway, or Both? Applying Transcriptomics for Chemical Hazard Assessment. Chairs: Jesse Rogers, Merck & Co. Inc.; Kristie Sullivan, Institute for In Vitro Sciences Inc.
Tuesday, March 24th, 4:30 PM to 6:00 PM, Ballroom 6E, Convention Center
SOT 2026 Theme 3: Navigating AI’s Promise, Practicality, and Pitfalls
AI offers vast opportunities to accelerate chemical safety assessment, enhance predictive accuracy, reduce reliance on animal testing, and increase workflow efficiency. But AI's predictive power in toxicology is only as good as the biological data it is trained on. Models trained on sparse or heterogeneous toxicity data inherit those limitations regardless of their sophistication. Conversely, models trained on large, well-characterized transcriptomic datasets, such as the recently published DILImap resource of 300 compounds profiled in primary human hepatocytes, have demonstrated striking early predictive power. Paired with the ToxPredictor AI model, it identified compounds like Fasiglifam (TAK-875), which appeared safe in standard preclinical models but failed in Phase III due to human-specific liver injury that animal studies missed entirely.
One Symposium session critically examines the limitations of AI in assessing complex biological systems, including persistent data scarcity, quality issues, application constraints, lack of transparency, and the current challenge in predicting emergent toxicological outcomes. The session promises to highlight best practices, validation requirements, and the responsible but impactful integration of AI in toxicology research and regulation.
A similar Continuing Education session explores the need for cross-functional teams, including computational, mechanistic toxicology, and environmental health scientists, to collaborate to accurately predict ADMET outcomes from data-rich assays like omics, cell painting, and beyond.
Learn more in our in-depth explainer on omics integration with AI article.
Recommended Sessions at SOT 2026:
- Symposium Session: AI in Toxicology: Navigating Promise, Pitfalls, and Practical Implementation. Chairs: Scott Auerbach, NIEHS/DTT; John Rooney, Syngenta Crop Protection LLC.
Monday, March 23rd, 2:00 PM to 4:45 PM, Ballroom 6B, Convention Center - Continuing Education Course AM03: Applications of Machine Learning and Artificial Intelligence Approaches to Advance Toxicology and Environmental Health Sciences. Chairs: Zhoumeng Lin, University of Florida; Nicole Kleinstreuer, NIH.
Sunday, March 22nd, 8:15 AM to 12:00 Noon, Ballroom 6F, Convention Center
Expected SOT Annual Meeting and ToxExpo Key Takeaways
- Transcriptomics and other omics modalities are transforming toxicology from descriptive observation to mechanistic and quantitative decision science
- NAMs + omics are gaining traction for more human-relevant safety risk mitigation, faster compound attrition, and better predictive power
- The regulatory landscape is increasingly embracing omics integration in toxicology
- AI models, when trained with sufficient data depth from omics technologies, stand to enhance predictive accuracy, but limitations must be carefully considered
Want a deeper dive into how transcriptomics enables better predictive power, detects toxicity missed by traditional methods, and gives systems-level mechanistic insights into compound effects? Check out our in-depth explainer article.
