Comparative study of (Q)SAR models for predicting the environmental fate of cosmetic ingredients: Persistence, bioaccumulation, and mobility
- Elena Fioravanzo
- Oct 13
- 2 min read
The regulatory landscape for the cosmetics industry continues to evolve, placing a heightened focus on the environmental fate of ingredients—specifically their Persistence (P), Bioaccumulation (B), and Mobility (M). With the EU ban on animal testing, (Quantitative) Structure-Activity Relationship ((Q)SAR) models and other New Approach Methodologies (NAMs) have become indispensable for filling critical data gaps.
We are delighted to highlight a highly valuable and well-executed study in this area: "Comparative study of (Q)SAR models for predicting the environmental fate of cosmetic ingredients: Persistence, bioaccumulation, and mobility," published in the NAM Journal (Volume 1, 2025, 100054).
This research provides a rigorous comparative analysis of five popular freeware QSAR tools (VEGA, EPI Suite™, T.E.S.T., ADMETLab 3.0, and Danish QSAR Models) specifically using a dataset of cosmetic ingredients.
You can access the full paper here: https://doi.org/10.1016/j.namjnl.2025.100054
Key Insights for Regulatory Risk Assessors
The study offers practical, model-specific guidance crucial for anyone performing environmental risk assessment (ERA) for cosmetics or chemicals subject to REACH and CLP criteria:
Persistence (P): The Ready Biodegradability IRFMN model (VEGA), Leadscope model (Danish QSAR Model), and BIOWIN (EPISUITE) showed the highest performance for persistence.
Bioaccumulation (B): For the critical Log Kow parameter, ALogP (VEGA), ADMETLab 3.0, and KOWWIN (EPISUITE) were top performers. For BCF prediction, Arnot-Gobas (VEGA) stood out.
Mobility (M): The VEGA OPERA and KOCWIN-Log Kow estimation models were identified as relevant for predicting mobility.
The Power of NAMs and the Applicability Domain
The authors confirm a vital principles we champion in our own training (Tutor-assisted eLearning courses for in silico toxicology), The Critical Role of the Applicability Domain (AD). The study strongly highlights that incorporating AD information into QSAR evaluations is essential. It allows toxicologists to scientifically justify the reliability of their predictions, which is non-negotiable for regulatory acceptance.
Our sincere thanks to Kevin Sulmona, Myriam Louazzani, José Ginestar, Pauline Lancia, Aurélie Baleydier, and the entire team for this important and transparent benchmarking exercise. Their work offers clarity in a complex area and will be a key resource for the industry.
Mastering QSAR and Read-Across with Our Training
Understanding which models to use, when to trust them, and how to define their limitations is a challenge in modern risk assessment.
This paper perfectly reinforces the structured approach taught in our course, "NAMs - Use and application of QSAR and read-across," https://courses.toxnavigation.com/course/nams. Our training equips you with the framework to critically evaluate and apply these tools—not just for cosmetics, but across all sectors where NAMs are essential.
Enroll today to learn how to expertly navigate the complex landscape of QSAR predictions for environmental fate and regulatory compliance.
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