Article
Water Resources
Denis Habauzit, Pierre Lemee, Luis M. Botana, Valerie Fessard
Summary: Climate change increases concerns about mycotoxins worldwide. Environmental changes affect crop growth, favoring fungi development and mycotoxin presence. In addition to direct oral exposure, human exposure to mycotoxins can occur through contaminated animal feed and consumption of meat or milk products. This study used validated in silico tools to assess the toxicity of mycotoxins. Out of 552 mycotoxins, 12 were found to have potential cancer-promoting activity, particularly in relation to lung cancer.
EXPOSURE AND HEALTH
(2023)
Article
Management
Gianluca Biggi, Elisa Giuliani, Arianna Martinelli, Emilio Benfenati
Summary: Researchers propose a method that combines patent analysis with computational toxicology to measure the chemical toxicity components within patents. By analyzing the toxicity of ten hazardous chemicals and comparing them with other groups of chemical patents, they suggest that this method could have significant policy implications for future research.
Review
Medicine, Legal
P. Suresh Jayasekara, Sophie K. Skanchy, Marlene T. Kim, Govindaraj Kumaran, Benon E. Mugabe, Lauren E. Woodard, Jian Yang, Andrew J. Zych, Naomi L. Kruhlak
Summary: The ICH M7 (R1) guideline recommends the use of complementary (Q)SAR models to assess mutagenic potential of drug impurities, with expert knowledge playing a crucial role in overturning and resolving predictions, especially for low confidence predictions.
REGULATORY TOXICOLOGY AND PHARMACOLOGY
(2021)
Article
Medicine, Legal
Hung-Lin Kan, Chia-Chi Wang, Ying-Chi Lin, Chun-Wei Tung
Summary: A QSAR model was developed to identify potential neurotoxicants, achieving a high accuracy of 87.7% in an independent test on 452 chemicals. The model was applied to 157 preservatives, identifying 15 chemicals potentially toxic to neuronal cells, with three of them further validated by in vitro experiments. Further experiments are recommended to assess the neurotoxicity of the identified preservatives with potential neuronal cytotoxicity.
REGULATORY TOXICOLOGY AND PHARMACOLOGY
(2021)
Article
Toxicology
Gul Karaduman, Feyza Kelleci Celik
Summary: By creating a QSAR model, the risk level of drugs during pregnancy can be predicted, providing guidance on the safe use of pharmaceuticals without the need for animal tests or clinical trials on pregnant women.
JOURNAL OF APPLIED TOXICOLOGY
(2023)
Article
Toxicology
Eric March-Vila, Giacomo Ferretti, Emma Terricabras, Ines Ardao, Jose Manuel Brea, Maria Jose Varela, Alvaro Arana, Juan Andres Rubiolo, Ferran Sanz, Maria Isabel Loza, Laura Sanchez, Hector Alonso, Manuel Pastor
Summary: In order to reduce the impact of human activity on the environment, many industries in the leather and textile sector are adopting measures to characterize the chemical safety of substances commonly used in their processes. This study compiles and annotates the substances used in this sector, using a combination of data collection, experimental methods, and in silico predictions. The results show that in silico methods can provide reasonably good hazard estimations and fill knowledge gaps in the chemical space of the leather and textile industry.
ARCHIVES OF TOXICOLOGY
(2023)
Article
Biochemistry & Molecular Biology
Fjodor Melnikov, Lennart T. T. Anger, Catrin Hasselgren
Summary: Due to challenges with historical data and assay formats, in silico models for safety endpoints often rely on discretized data. However, these models have limitations that affect compound design. In this study, a consistent data inference approach was used to estimate IC50 for hERG inhibition. The resulting models showed high accuracy and can be valuable in pharmaceutical projects for compound ranking and evaluation against specific inhibition thresholds.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Review
Environmental Sciences
Sang Hee Lee, Jongwoon Kim, Jinyong Kim, Jaehyun Park, Sanghee Park, Kyu-Bong Kim, Byung-Mu Lee, Seok Kwon
Summary: In this study, the current application status of Structure Activity Relationship (SAR)-based read-across in the Republic of Korea (ROK) was examined in terms of chemical risk assessments and registrations. The Ministry of Environment (MOE) and the Ministry of Food and Drug Safety (MFDS) are both considering the use of read-across approaches in their regulatory processes. However, the limitations of read-across, such as the lack of standardized acceptance criteria and inconsistencies in scientific evidence, must be addressed. Cooperative efforts from regulatory agencies, academia, and industry are necessary to improve the quality and acceptance of read-across data.
JOURNAL OF TOXICOLOGY AND ENVIRONMENTAL HEALTH-PART B-CRITICAL REVIEWS
(2022)
Review
Biochemistry & Molecular Biology
Sarfaraz K. Niazi, Zamara Mariam
Summary: In modern drug discovery, the combination of chemoinformatics and quantitative structure-activity relationship (QSAR) modeling has become a powerful alliance for predictive molecular design and analysis using machine learning techniques. This review explores the fundamental aspects of chemoinformatics and the crucial role of molecular descriptors in uncovering molecular properties. It also discusses the technical intricacies of developing robust ML-QSAR models and showcases various ML algorithms for predicting and understanding the relationships between molecular structures and biological activities. This review serves as a comprehensive guide for researchers, highlighting the synergy between chemoinformatics, QSAR, and ML and its potential for expediting the discovery of novel therapeutic agents.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Article
Medicine, Legal
Jessica C. Graham, Maryann Rodas, Jedd Hillegass, Gene Schulze
Summary: Acute oral toxicity (AOT) information is used for compound classification and hazard evaluation, with in silico models being developed to predict AOT and reduce reliance on animal testing. Using historical data, the study found that these in silico models can effectively identify compounds with low acute oral toxicity and assist in determining starting doses for in vivo AOT studies.
REGULATORY TOXICOLOGY AND PHARMACOLOGY
(2021)
Review
Toxicology
Zhoumeng Lin, Wei-Chun Chou
Summary: The application of machine learning and artificial intelligence in toxicology has revolutionized the field, enabling efficient development of models, accurate toxicity prediction, and in-depth analysis of various types of data.
TOXICOLOGICAL SCIENCES
(2022)
Article
Toxicology
Michael F. Santillo, Robert L. Sprando
Summary: There has been a rise in cannabis-derived products being sold as food and dietary supplements. A study used an in silico tool to predict the binding between 55 cannabinoids and 4,799 biological targets. The predictions were validated with in vitro binding data, and clinical adverse effects associated with the predicted targets were identified.
JOURNAL OF APPLIED TOXICOLOGY
(2023)
Article
Toxicology
Giselle R. M. Bellia, Robert A. A. Bilott, Ning Sun, David Thompson, Vasilis Vasiliou
Summary: Current literature suggests that PFAS carbon chain length may affect its toxicity, and statistical modeling can be used to predict toxicity and improve the efficiency of PFAS regulation development. In this study, data analysis and predictive modeling were conducted, showing significant differences in mean values for 11 out of 15 health outcomes. Simple linear regressions were used for two health outcomes, yielding statistically significant results. Comparison between the results of an actual dataset and a theoretically generated dataset indicated no significant differences in the mean values of the two health outcomes. Therefore, predictive statistical modeling can be used to predict health outcomes for PFAS exposure.
TOXICOLOGY MECHANISMS AND METHODS
(2023)
Article
Environmental Sciences
Jochen P. Zubrod, Nika Galic, Maxime Vaugeois, David A. Dreier
Summary: A major challenge in ecological risk assessment is estimating chemical-induced effects across taxa without species-specific testing. Our study utilized existing knowledge about organismal physiology to understand and predict differences in species sensitivity. Machine learning models were trained to predict chemical- and species-specific endpoints based on both chemical fingerprints and physiological properties.
ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY
(2023)
Review
Toxicology
Natalia Lidmar von Ranke, Reinaldo Barros Geraldo, Andre Lima dos Santos, Victor G. O. Evangelho, Flaminia Flammini, Lucio Mendes Cabral, Helena Carla Castro, Carlos Rangel Rodrigues
Summary: This paper reviews the use of computational approaches for nanotoxicology prediction and discusses the characteristics of various computational methods used in nanomaterial analysis. It also describes the application of data integration methods in nanotoxicology.
COMPUTATIONAL TOXICOLOGY
(2022)
Article
Pharmacology & Pharmacy
Thomas Steinbach, Samantha Gad-McDonald, Naomi Kruhlak, Mark Powley, Nigel Greene
INTERNATIONAL JOURNAL OF TOXICOLOGY
(2015)
Article
Medicine, Legal
Nigel Greene, Krista L. Dobo, Michelle O. Kenyon, Jennifer Cheung, Jennifer Munzner, Zhanna Sobol, Gregory Sluggett, Todd Zelesky, Andreas Sutter, Joerg Wichard
REGULATORY TOXICOLOGY AND PHARMACOLOGY
(2015)
Article
Toxicology
Falgun Shah, Louis Leung, Hugh A. Barton, Yvonne Will, A. David Rodrigues, Nigel Greene, Michael D. Aleo
TOXICOLOGICAL SCIENCES
(2015)
Review
Toxicology
Nigel Greene, William Pennie
TOXICOLOGY RESEARCH
(2015)
Article
Medicine, Legal
Chris Barber, Alex Cayley, Thierry Hanser, Alex Harding, Crina Heghes, Jonathan D. Vessey, Stephane Werner, Sandy K. Weiner, Joerg Wichard, Amanda Giddings, Susanne Glowienke, Alexis Parenty, Alessandro Brigo, Hans-Peter Spirkl, Alexander Amberg, Ray Kemper, Nigel Greene
REGULATORY TOXICOLOGY AND PHARMACOLOGY
(2016)
Article
Medicine, Legal
Richard V. Williams, Alexander Amberg, Alessandro Brigo, Laurence Coquin, Amanda Giddings, Susanne Glowienke, Nigel Greene, Robert Jolly, Ray Kemper, Catherine O'Leary-Steele, Alexis Parenty, Hans-Peter Spirkl, Susanne A. Stalford, Sandy K. Weiner, Joerg Wichard
REGULATORY TOXICOLOGY AND PHARMACOLOGY
(2016)
Article
Medicine, Legal
Lynne D. Butler, Peggy Guzzie-Peck, James Hartke, Matthew S. Bogdanffy, Yvonne Will, Dolores Diaz, Elisabeth Mortimer-Cassen, Mazin Derzi, Nigel Greene, Joseph J. DeGeorge
REGULATORY TOXICOLOGY AND PHARMACOLOGY
(2017)
Article
Chemistry, Medicinal
Falgun Shah, Shirley Louise-May, Nigel Greene
BIOORGANIC & MEDICINAL CHEMISTRY LETTERS
(2014)
Article
Chemistry, Medicinal
Falgun Shah, Nigel Greene
CHEMICAL RESEARCH IN TOXICOLOGY
(2014)
Review
Pharmacology & Pharmacy
Iskander Yusof, Falgun Shah, Tatsu Hashimoto, Matthew D. Segall, Nigel Greene
DRUG DISCOVERY TODAY
(2014)
Editorial Material
Environmental Sciences
Luoping Zhang, Cliona M. McHale, Nigel Greene, Ronald D. Snyder, Ivan N. Rich, Marilyn J. Aardema, Shambhu Roy, Stefan Pfuhler, Sundaresan Venkatactahalam
ENVIRONMENTAL AND MOLECULAR MUTAGENESIS
(2014)
Article
Medicine, Legal
Andreas Sutter, Alexander Amberg, Scott Boyer, Alessandro Brigo, Joseph F. Contrera, Laura L. Custer, Krista L. Dobo, Veronique Gervais, Susanne Glowienke, Jacky van Gompel, Nigel Greene, Wolfgang Muster, John Nicolette, M. Vijayaraj Reddy, Veronique Thybaud, Esther Vock, Angela T. White, Lutz Mueller
REGULATORY TOXICOLOGY AND PHARMACOLOGY
(2013)
Article
Toxicology
Russell T. Naven, Rachel Swiss, Jacquelyn Klug-Mcleod, Yvonne Will, Nigel Greene
TOXICOLOGICAL SCIENCES
(2013)
Article
Toxicology
Arianna Bassan, Vinicius M. Alves, Alexander Amberg, Lennart T. Anger, Scott Auerbach, Lisa Beilke, Andreas Bender, Mark T. D. Cronin, Kevin P. Cross, Jui-Hua Hsieh, Nigel Greene, Raymond Kemper, Marlene T. Kim, Moiz Mumtaz, Tobias Noeske, Manuela Pavan, Julia Pletz, Daniel P. Russo, Yogesh Sabnis, Markus Schaefer, David T. Szabo, Jean-Pierre Valentin, Joerg Wichard, Dominic Williams, David Woolley, Craig Zwickl, Glenn J. Myatt
Summary: Hepatotoxicity is a common adverse effect observed from exposure to xenobiotics, particularly in pharmaceutical research where it can lead to drug withdrawals, clinical failures, and discontinuation of drug candidates. More sustainable and informative methods for assessing hepatotoxicity are critically needed.
COMPUTATIONAL TOXICOLOGY
(2021)
Article
Medicine, Research & Experimental
Olga Obrezanova, Anton Martinsson, Tom Whitehead, Samar Mahmoud, Andreas Bender, Filip Miljkovic, Piotr Grabowski, Ben Irwin, Ioana Oprisiu, Gareth Conduit, Matthew Segall, Graha M. F. Smith, Beth Williamson, Susanne Winiwarter, Nigel Greene
Summary: In this study, machine learning models were developed to predict rat in vivo pharmacokinetic parameters and concentration-time profiles based on molecular structure and in vitro parameters. The models showed better performance compared to traditional machine learning algorithms and deep learning approaches, providing a useful tool for drug design and compound prioritization.
MOLECULAR PHARMACEUTICS
(2022)