Developing a Novel Read-Across Concept for Ecotoxicological Risk Assessment of Phosphate Chemicals: A Case Study

Author:

Lee Seokwon1ORCID,Ok Seung-Yeop23,Moon Hyo-Bang3,Seo Sung-Chul4,Ra Jin-Sung5

Affiliation:

1. Geum River Environment Research Center, National Institute of Environmental Research, Okcheon-gun 29027, Chungbuk, Republic of Korea

2. Department of Environmental Fate and Modelling, Knoell Korea Ltd., Seoul 07327, Republic of Korea

3. Department of Marine Sciences and Convergent Engineering, Hanyang University, Ansan 15588, Republic of Korea

4. Department of Nano, Chemical and Biological Engineering, College of Engineering, Seokyeong University, Seoul 02173, Republic of Korea

5. Regulatory Chemical Analysis & Risk Assessment Center, Korea Institute of Industrial Technology (KITECH), Ansan 15588, Republic of Korea

Abstract

This study introduces a novel concept approach for a read-across assessment, considering species sensitivity differences among phosphate chemicals within structurally similar compound groups. Twenty-five organic chemicals, with a log Kow of 5 or less, were categorized into three functional groups based on acetylcholinesterase (AChE) inhibition as a specific mode of action (MOA). The short-term aquatic toxicity data (LC50) for fish, crustaceans, and insects were collected from the U.S. EPA Ecotoxicology (ECOTOX) Knowledgebase. A geometric mean calculation method was applied for multiple toxic endpoints. Performance metrics for the new read-across concept, including correlation coefficient, bias, precision, and accuracy, were calculated. Overall, a slightly higher overestimation (49.2%) than underestimation (48.4%) in toxicity predictions was observed in two case studies. In Case study I, a strong positive correlation (r = 0.93) between the predicted and known toxicity values of target chemicals was observed, while in Case study II, with limited information on species and their ecotoxicity, showed a moderate correlation (r = 0.75). Overall, the bias and precision for Case study I were 0.32 ± 0.01, while Case study II showed 0.65 ± 0.06; however, the relative bias (%) increased from 37.65% (Case study I) to 91.94% (Case study II). Bland–Altman plots highlight the mean differences of 1.33 (Case study I) and 1.24 (Case study II), respectively. The new read-across concept, focusing on AChE inhibition and structural similarity, demonstrated good reliability, applicability, and accuracy with minimal bias. Future studies are needed to evaluate various types of chemical substances, diverse modes of action, functional groups, toxic endpoints, and test species to ensure overall comprehensiveness and robustness in toxicity predictions.

Funder

National Institute of Environmental Research

Publisher

MDPI AG

Reference42 articles.

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2. United States Environmental Protection Agency (2023, December 01). Compliance Guide for the Chemical Import Requirements of the Toxic Substances Control Act (TSCA). No. EPA 305-B-08-001, Available online: https://www.epa.gov/compliance/compliance-guide-chemical-import-requirements-toxic-substances-control-act.

3. EC (2003). Technical Guidance Document Part I in Support of the Commission Directive 93/67/EEC on Risk Assessment for New Notified Substances and Commission Regulation No. 1488/94 on Risk Assessment for Existing Substances, Office for Publications of the European Communities.

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