Predicting Prenatal Developmental Toxicity Based On the Combination of Chemical Structures and Biological Data

Autor: Heather L. Ciallella, Daniel P. Russo, Swati Sharma, Yafan Li, Eddie Sloter, Len Sweet, Heng Huang, Hao Zhu

Publikováno v: Environ Sci Technol

For hazard identification, classification, and labeling purposes, animal testing guidelines are required by law to evaluate the developmental toxicity potential of new and existing chemical products. However, guideline developmental toxicity studies

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a9ce8b03ddfd97397ad5bdc4d5c09a4a
https://pubmed.ncbi.nlm.nih.gov/35451820

Predictive modeling of estrogen receptor agonism, antagonism, and binding activities using machine- and deep-learning approaches

Autor: Daniel P. Russo, Heather L. Ciallella, Hao Zhu, Fabian A. Grimm, Lauren M. Aleksunes

Publikováno v: Laboratory investigation; a journal of technical methods and pathology

As defined by the World Health Organization, an endocrine disruptor is an exogenous substance or mixture that alters function(s) of the endocrine system and consequently causes adverse health effects in an intact organism, its progeny, or (sub)popula

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::36077c2c2837df48f4939611baac2513
https://doi.org/10.1038/s41374-020-00477-2

Automatic Quantitative Structure-Activity Relationship Modeling to Fill Data Gaps in High-Throughput Screening

Autor: Heather L, Ciallella, Elena, Chung, Daniel P, Russo, Hao, Zhu

Publikováno v: Methods in molecular biology (Clifton, N.J.). 2474

Advances in high-throughput screening (HTS) revolutionized the environmental and health sciences data landscape. However, new compounds still need to be experimentally synthesized and tested to obtain HTS data, which will still be costly and time-con

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=pmid________::41218e24f1dbaa0b6ea56313432a0bc5
https://pubmed.ncbi.nlm.nih.gov/35294765

CATMoS: Collaborative Acute Toxicity Modeling Suite

Autor: Tyler Peryea, Ahsan Habib Polash, Alessandra Roncaglioni, Daniel M. Wilson, Warren Casey, Patricia Ruiz, Nathalie Alépée, Sherif Farag, Giovanna J. Lavado, Kimberley M. Zorn, Alexey V. Zakharov, Davide Ballabio, Katrina M. Waters, Risa Sayre, Giuseppe Felice Mangiatordi, Orazio Nicolotti, Nicole Kleinstreuer, Pankaj R. Daga, Sean Ekins, Kamel Mansouri, Liguo Wang, Judy Strickland, Matthew J. Hirn, Sudin Bhattacharya, Dac-Trung Nguyen, Emilio Benfenati, Ignacio J. Tripodi, Amanda K. Parks, Garett Goh, Dennis G. Thomas, Glenn J. Myatt, Prachi Pradeep, Gergely Zahoranszky-Kohalmi, Anton Simeonov, Arthur C. Silva, Grace Patlewicz, Timothy Sheils, Stephen Boyd, Agnes L. Karmaus, Ahmed Sayed, Alex M. Clark, Todd M. Martin, Pavel Karpov, Jeffery M. Gearhart, Robert Rallo, D Allen, Charles Siegel, Zhen Zhang, Zijun Xiao, Alexander Tropsha, Stephen J. Capuzzi, Alexandru Korotcov, Carolina Horta Andrade, Noel Southall, Viviana Consonni, Igor V. Tetko, Jeremy M. Fitzpatrick, Andrew J. Wedlake, Denis Fourches, Zhongyu Wang, Vinicius M. Alves, Eugene N. Muratov, Timothy E. H. Allen, Andrea Mauri, James B. Brown, Alexandre Varnek, Yun Tang, Sanjeeva J. Wijeyesakere, Daniel P. Russo, Cosimo Toma, Christopher M. Grulke, Michael S. Lawless, Domenico Gadaleta, Paritosh Pande, Thomas Hartung, Jonathan M. Goodman, Kristijan Vukovic, Joyce V. Bastos, Daniela Trisciuzzi, Fagen F. Zhang, Domenico Alberga, Thomas Luechtefeld, Dan Marsh, Tyler R. Auernhammer, Shannon M. Bell, Xinhao Li, Brian J. Teppen, F. Lunghini, Sergey Sosnin, Hao Zhu, Feng Gao, Craig Rowlands, Tongan Zhao, R Todeschini, Valery Tkachenko, Francesca Grisoni, Hongbin Yang, Yaroslav Chushak, Maxim V. Fedorov, Heather L. Ciallella, Gilles Marcou

Publikováno v: Environmental Health Perspectives
Environmental Health Perspectives, National Institute of Environmental Health Sciences, 2021, 129 (4), pp.047013. ⟨10.1289/EHP8495⟩

BACKGROUND: Humans are exposed to tens of thousands of chemical substances that need to be assessed for their potential toxicity. Acute systemic toxicity testing serves as the basis for regulatory hazard classification, labeling, and risk management.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6f10be9a3f401d14e1b5653e1242ab66
https://www.repository.cam.ac.uk/handle/1810/322114

Advancing Computational Toxicology in the Big Data Era by Artificial Intelligence: Data-Driven and Mechanism-Driven Modeling for Chemical Toxicity

Autor: Heather L. Ciallella, Hao Zhu

Publikováno v: Chemical research in toxicology. 32(4)

In 2016, the Frank R. Lautenberg Chemical Safety for the 21st Century Act became the first US legislation to advance chemical safety evaluations by utilizing novel testing approaches that reduce the testing of vertebrate animals. Central to this miss

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e838492284123901222620a67fe9852c
https://pubmed.ncbi.nlm.nih.gov/30907586