Imagine a world where every chemical we produce—from life-saving medicines to crop-protecting pesticides—leaves an invisible fingerprint on our environment. These substances, once released, travel through ecosystems, affecting organisms from microscopic algae to humans. Ecotoxicology, the science that studies these effects, provides critical insights that guide environmental decision-making worldwide. This field helps us understand the delicate balance between technological progress and environmental protection, offering data-driven solutions to some of our most pressing planetary challenges 1 .
Chemicals in global trade with insufficient hazard assessment data 6
The significance of ecotoxicology has never been more apparent. With approximately 350,000 chemicals in global trade and only 3.5% having sufficient data for proper hazard assessment, researchers face a monumental task in protecting ecosystems from potential harm 6 . Through innovative approaches ranging from molecular biology to machine learning, ecotoxicologists are developing the tools and knowledge needed to navigate this complex landscape, ensuring that environmental decisions are based on solid science rather than guesswork.
Ecotoxicology combines elements of ecology, toxicology, chemistry, and environmental science to study the effects of toxic chemicals on biological organisms, particularly within the context of populations, communities, and entire ecosystems.
At the heart of ecotoxicology lies the tiered risk assessment approach, which typically begins with rapid screening tools requiring minimal data, followed by more detailed and complex assessments for selected chemicals and scenarios 1 .
Environmental protection agencies worldwide rely on ecotoxicological data to regulate chemicals. The United States Environmental Protection Agency (EPA), for example, uses tools like the ECOTOX Knowledgebase (a comprehensive database of chemical effects on aquatic and terrestrial species) and the Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool (which extrapolates toxicity information across species) 1 . Similarly, the European Chemicals Agency implements REACH (Registration, Evaluation, Authorisation and Restriction of Chemicals) regulations that require extensive ecotoxicological testing for market approval.
A 2025 study demonstrated how machine learning techniques could bridge critical data gaps in ecotoxicological hazard assessment, predicting missing ecotoxicity data by learning patterns from existing tested chemical-species pairs 6 .
Extracted data from the ADORE dataset including 70,670 experiments with 18,966 unique chemical-species pairs across 3,295 chemicals and 1,267 species 6 .
LC50 values were log-transformed and organized into a sparse matrix where most chemical-species pairs lacked experimental data.
Used a Bayesian matrix factorization approach adapted for pairwise learning, treating chemical identities, species identities, and exposure durations as categorical variables.
Employed rigorous cross-validation techniques and generated practical outputs including Hazard Heatmaps and Species Sensitivity Distributions.
The study generated more than four million predicted LC50 values for previously untested chemical-species pairs, dramatically expanding the available ecotoxicological information 6 . Validation results demonstrated that the pairwise learning approach significantly outperformed simpler modeling techniques.
This research represents a paradigm shift in ecotoxicological hazard assessment. By leveraging machine learning to predict rather than measure all necessary data, the approach addresses the fundamental impossibility of experimentally testing all chemical-species combinations.
Ecotoxicologists employ a diverse array of tools and methodologies to assess chemical impacts on environments. The following table highlights key research solutions used in modern ecotoxicological studies:
| Tool Category | Specific Tool/Resource | Function and Application | Regulatory Relevance |
|---|---|---|---|
| Database Resources | ECOTOX Knowledgebase | Comprehensive database of single chemical toxicity effects on aquatic and terrestrial species | EPA risk assessments |
| Database Resources | CompTox Chemicals Dashboard | Curated data on chemical properties, hazards, exposures, and risk assessments | Chemical prioritization |
| Prediction Tools | SeqAPASS | Extrapolates toxicity information across species using protein sequence alignment | Species extrapolation |
| Prediction Tools | Web-ICE | Estimates acute toxicity to aquatic and terrestrial organisms using interspecies correlation | Data gap filling |
| Experimental Models | Markov Chain Nest (MCnest) | Estimates impact of pesticide exposures on avian reproductive success | Bird population risk assessment |
| Omics Technologies | Transcriptomics | Measures gene expression changes in response to chemical exposure | Mechanism elucidation |
Ecotoxicological research has revealed concerning information about pharmaceutical pollution, particularly regarding medicines listed on Essential Medicines Lists (EMLs) used by 158 countries worldwide 5 . A 2025 study identified five medicines—ciprofloxacin, ethinylestradiol, levonorgestrel, ibuprofen, and sertraline—as particularly concerning due to their high environmental persistence and toxicity.
Policy ImpactModern ecotoxicology doesn't examine chemical impacts in isolation but considers interacting stressors like climate change 1 . Researchers are developing models that integrate temperature changes, ocean acidification, and other climate-related factors with chemical exposure scenarios.
Research InnovationThe SETAC Europe 2025 session on "Molecular Ecotoxicology and Omics Perspectives" highlighted exciting advances in applying molecular tools to environmental risk assessment 2 . These approaches include:
Regulatory agencies are increasingly embracing New Approach Methods that reduce animal testing while improving human and ecological relevance 3 . The EPA's extensive NAMs training program includes tools like:
Ecotoxicology provides the scientific foundation for environmental decision-making in an increasingly chemical-intensive world. From traditional toxicity testing with algae, Daphnia, and fish 4 to cutting-edge machine learning approaches that predict effects across thousands of untested chemical-species combinations 6 , the field continues to evolve to meet emerging challenges.
The future of ecotoxicology lies in integrating approaches—combining traditional methods with novel computational tools, molecular analyses, and cross-species extrapolation techniques to create a more comprehensive understanding of chemical impacts. This integration will enable smarter regulatory decisions, more sustainable chemical design, and ultimately better protection for Earth's precious ecosystems.