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REVIEW article

Front. Toxicol.

Sec. Computational Toxicology and Informatics

Volume 7 - 2025 | doi: 10.3389/ftox.2025.1632941

Advancing Human health Risk Assessment: The Role of New Approach Methodology

Provisionally accepted
  • 1Pere Virgili Health Research Institute (IISPV), Tarragona, Spain
  • 2German Federal Institute for Risk Assessment (BfR), Berlin, Germany
  • 3Universitat Rovira i Virgili, Center of Environmental, Food and Toxicological Technology (TECNATOX),, Tarragona, Spain
  • 4Escola Politècnica d’Enginyeria de Vilanova i la Geltrú (EPSEVG-GiES), Universitat Politècnica de Catalunya, Víctor Balaguer, 1, 08800, Vilanova i la Geltrú, Spain

The final, formatted version of the article will be published soon.

New Approach Methodologies (NAMs) hold great potential to fill data gaps for chemicals and 2 modernisation of chemical risk assessment practices. Current toxicity testing is based on 3 conventional approaches with high reliability on in-vivo studies, but with time, regulators are 4 trying to move towards in-vitro and in-silico tools enabling efficient risk assessment 5 strategies. Herein, we discuss about different emerging techniques which are or can become 6 a NAM including both in-vitro and in-silico models with particular focus on reducing animal 7 studies and improving decision-making for hazard and exposure assessment. We also 8 discussed about the way to strengthen the regulatory and public confidence in different 9 NAMs and automation of these approaches. Some of these NAMs can help in identifying 10 biochemical mechanisms for toxicity, calculate the point of departure (PoD), develop 11 adverse outcome pathways (AOP), translate risk to multiple species and quantify 12 uncertainty from predictions for multiple chemicals. Scientists and regulators can work 13 together to frame robust guidelines for the practical application of these tools and ensure 14 reproducible results.

Keywords: New approach methodology (NAM), Point of departure (POD), In-vitro, omics, In-silico, machine learning, data harmonization

Received: 22 May 2025; Accepted: 18 Sep 2025.

Copyright: © 2025 DEEPIKA, Bharti, Sharma, Kumar, Pathak, Biosca Brull, Sabuz, García Vilana and Kumar. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Vikas Kumar, vikas.kumar@urv.cat

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