New Models and Applications in Predictive Toxicology

A special issue of Toxics (ISSN 2305-6304). This special issue belongs to the section "Novel Methods in Toxicology Research".

Deadline for manuscript submissions: closed (28 February 2024) | Viewed by 5588

Special Issue Editors


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Guest Editor
College of Public Health, University of South Florida College, Tampa, FL, USA
Interests: toxicology; food safety; molecular biology; chemical safety; environmental toxicology

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Guest Editor
US Food & Drug Administration (FDA) COLLEGE PK, Silver Spring, MD, USA
Interests: food toxicology; risk communication; new methods

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Guest Editor
US Food & Drug Administration (FDA) COLLEGE PK, Silver Spring, MD, USA
Interests: predictive toxicology

Special Issue Information

Dear Colleagues,

New approach methods (NAMs) are technologies and approaches, including computational modeling, in vitro assays, microphysiological systems, or testing using alternative animal species such as zebrafish that are predictive of hazard without the use of traditional animal studies. The FDA and other regulators worldwide will incorporate NAMS into regulatory assessments if certain data requirements are met. Regulators are adopting a context-of-use or fit-for-purpose approach. Any new method should have a clearly articulated description of the purpose for a particular new approach. It ideally should delineate the regulatory question or gaps to which the resulting data can be applied. The crucial question that new approach methods must answer are whether the data generated are predictive of and are translatable to humans (or pets or food animals). These are essential performance criteria for the acceptance of a new method into the regulatory paradigm. To be accepted into the regulatory process, it is anticipated that each NAM will be required to demonstrate a qualification program that incorporates several known chemicals, including both positive and negative controls that evaluate sensitivity and specificity.

The papers in this Special Edition will describe different emerging NAMs and how they can be used with confidence to answer regulatory decisions or fill regulator gaps. Of special interest will be the evaluation of NAMs for relevance to humans with or without using animals as the gold standard. Case studies of both successes and failures of the qualification process will be included in the issue.

Dr. A. Wallace Hayes
Dr. Steven J. Hermansky
Dr. Suzanne Compton Fitzpatrick
Guest Editors

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Keywords

  • 3 Rs
  • in vivo
  • in silico
  • context of use
  • fit for purpose

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Published Papers (4 papers)

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Research

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16 pages, 2671 KiB  
Article
The Fibrotic Phenotype of Human Precision-Cut Lung Slices Is Maintained after Cryopreservation
by Méry Marimoutou, Vivek Patel, Jae Hun Kim, Niccole Schaible, Jose Alvarez, Joseph Hughes, McKenzie Obermok, Carlos Iván Rodríguez, Thomas Kallarakal, Béla Suki, Khalid Amin, Ramaswamy Krishnan and Holger Peter Behrsing
Toxics 2024, 12(9), 637; https://doi.org/10.3390/toxics12090637 - 30 Aug 2024
Viewed by 857
Abstract
Human precision-cut lung slices (hPCLS) prepared from fibrotic lungs recapitulate the pathophysiological hallmarks of fibrosis. These hallmark features can also be induced by treating non-fibrotic hPCLS with a fibrotic cocktail (FC). As a result, the fibrotic and fibrosis-induced hPCLS are rapidly emerging as [...] Read more.
Human precision-cut lung slices (hPCLS) prepared from fibrotic lungs recapitulate the pathophysiological hallmarks of fibrosis. These hallmark features can also be induced by treating non-fibrotic hPCLS with a fibrotic cocktail (FC). As a result, the fibrotic and fibrosis-induced hPCLS are rapidly emerging as preferred models for disease modeling and drug discovery. However, current hPCLS models are limited by tissue viability in culture, as they are usually only viable for one week after harvesting. Here, we demonstrate that the fibrotic hPCLS can be cryopreserved, stored for months, and then thawed on demand without loss of hPCLS viability or protein content for 14 days post-thawing. Cryopreservation also preserves the pro-fibrotic potential of non-fibrotic hPCLS. Specifically, when we treated the thawed non-fibrotic hPCLS with an FC, we observed significant pro-fibrotic cytokine secretion and elevated tissue stiffness. These pro-fibrotic changes were inhibited by the small-molecule tyrosine kinase inhibitor, Nintedanib. Taken together, our work indicates that a feasible solution to prolong the pre-clinical utility of fibrotic and fibrosis-induced hPCLS is cryopreservation. We anticipate that cryopreserved hPCLS will serve as an advantageous predictive model for the evaluation of pro-fibrotic pathways during acute and chronic toxicity testing. Full article
(This article belongs to the Special Issue New Models and Applications in Predictive Toxicology)
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9 pages, 943 KiB  
Article
Models for the No-Observed-Effect Concentration (NOEC) and Maximal Half-Effective Concentration (EC50)
by Nadia Iovine, Alla P. Toropova, Andrey A. Toropov, Alessandra Roncaglioni and Emilio Benfenati
Toxics 2024, 12(6), 425; https://doi.org/10.3390/toxics12060425 - 12 Jun 2024
Viewed by 766
Abstract
Typical in silico models for ecotoxicology focus on a few endpoints, but there is a need to increase the diversity of these models. This study proposes models using the NOEC for the harlequin fly (Chironomus riparius) and EC50 for swollen duckweed [...] Read more.
Typical in silico models for ecotoxicology focus on a few endpoints, but there is a need to increase the diversity of these models. This study proposes models using the NOEC for the harlequin fly (Chironomus riparius) and EC50 for swollen duckweed (Lemna gibba) for the first time. The data were derived from the EFSA OpenFoodTox database. The models were based on the correlation weights of molecular features used to calculate the 2D descriptor in CORAL software. The Monte Carlo method was used to calculate the correlation weights of the algorithms. The determination coefficients of the best models for the external validation set were 0.74 (NOAEC) and 0.85 (EC50). Full article
(This article belongs to the Special Issue New Models and Applications in Predictive Toxicology)
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12 pages, 1481 KiB  
Communication
Integration of the Natural Language Processing of Structural Information Simplified Molecular-Input Line-Entry System Can Improve the In Vitro Prediction of Human Skin Sensitizers
by Jae-Hee Kwon, Jihye Kim, Kyung-Min Lim and Myeong Gyu Kim
Toxics 2024, 12(2), 153; https://doi.org/10.3390/toxics12020153 - 16 Feb 2024
Cited by 1 | Viewed by 1493
Abstract
Natural language processing (NLP) technology has recently used to predict substance properties based on their Simplified Molecular-Input Line-Entry System (SMILES). We aimed to develop a model predicting human skin sensitizers by integrating text features derived from SMILES with in vitro test outcomes. The [...] Read more.
Natural language processing (NLP) technology has recently used to predict substance properties based on their Simplified Molecular-Input Line-Entry System (SMILES). We aimed to develop a model predicting human skin sensitizers by integrating text features derived from SMILES with in vitro test outcomes. The dataset on SMILES, physicochemical properties, in vitro tests (DPRA, KeratinoSensTM, h-CLAT, and SENS-IS assays), and human potency categories for 122 substances sourced from the Cosmetics Europe database. The ChemBERTa model was employed to analyze the SMILES of substances. The last hidden layer embedding of ChemBERTa was tested with other features. Given the modest dataset size, we trained five XGBoost models using subsets of the training data, and subsequently employed bagging to create the final model. Notably, the features computed from SMILES played a pivotal role in the model for distinguishing sensitizers and non-sensitizers. The final model demonstrated a classification accuracy of 80% and an AUC-ROC of 0.82, effectively discriminating sensitizers from non-sensitizers. Furthermore, the model exhibited an accuracy of 82% and an AUC-ROC of 0.82 in classifying strong and weak sensitizers. In summary, we demonstrated that the integration of NLP of SMILES with in vitro test results can enhance the prediction of health hazard associated with chemicals. Full article
(This article belongs to the Special Issue New Models and Applications in Predictive Toxicology)
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Review

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20 pages, 825 KiB  
Review
Advancing Endocrine Disruptors via In Vitro Evaluation: Recognizing the Significance of the Organization for Economic Co-Operation and Development and United States Environmental Protection Agency Guidelines, Embracing New Assessment Methods, and the Urgent Need for a Comprehensive Battery of Tests
by Sophie Fouyet, Marie-Caroline Ferger, Pascale Leproux, Patrice Rat and Mélody Dutot
Toxics 2024, 12(3), 183; https://doi.org/10.3390/toxics12030183 - 28 Feb 2024
Viewed by 1810
Abstract
Efforts are being made globally to improve the evaluation and understanding of endocrine-disrupting chemicals. Recognition of their impact on human health and the environment has stimulated attention and research in this field. Various stakeholders, including scientists, regulatory agencies, policymakers, and industry representatives, are [...] Read more.
Efforts are being made globally to improve the evaluation and understanding of endocrine-disrupting chemicals. Recognition of their impact on human health and the environment has stimulated attention and research in this field. Various stakeholders, including scientists, regulatory agencies, policymakers, and industry representatives, are collaborating to develop robust methodologies and guidelines for assessing these disruptors. A key aspect of these efforts is the development of standardized testing protocols and guidelines that aim to provide consistent and reliable methods for identifying and characterizing endocrine disruptors. When evaluating the potential endocrine-disrupting activity of chemicals, no single test is capable of detecting all relevant endocrine-disrupting agents. The test battery approach is designed to reduce the risk of false negative results for compounds with toxic potential. A weight-of-evidence approach is therefore necessary for endocrine disruptor evaluation. This approach considers various types of data from multiple sources, assessing the overall strength, consistency, and reliability of the evidence. OECD guidelines are highly regarded for their scientific rigor, transparency, and consensus-based development process. It is crucial to explore and develop new methodologies that can effectively evaluate the risks associated with potential endocrine disruptors. Integrating these methods into a comprehensive weight-of-evidence framework will enhance risk assessments and facilitate informed decisions regarding the regulation and management of these substances, ensuring the protection of human health and the environment from their adverse effects. Full article
(This article belongs to the Special Issue New Models and Applications in Predictive Toxicology)
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