Acute Toxicity Prediction in Multiple Species by Leveraging Mechanistic ToxCast Mitochondrial Inhibition Data and Simulation of Oral Bioavailability

Bhhatarai, Barun; Wilson, Daniel M.; Bartels, Michael; Chaudhuri, Shubhra; Price, Paul S.; Carney, Edward W.

doi:10.1093/toxsci/kfv135

Cited by 18 publications

(16 citation statements)

References 37 publications

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“…The assay identified many substances that induce mitochondrial dysfunction, demonstrating its ability to reproducibly and rapidly detect substances that decrease mitochondrial membrane-potential (Attene-Ramos, Huang et al 2015). The data generated by this assay also correlated well with the existing fish, daphnia, and rat (intravenous) acute toxicity results (Bhhatarai, Wilson et al 2015), suggesting that a MMP assay could serve as an alternative for acute toxicity testing.…”

Section: Using Mechanisms and Adverse Outcome Pathways To Integratsupporting

confidence: 63%

Alternative approaches for identifying acute systemic toxicity: Moving from research to regulatory testing

Hamm

Sullivan

Clippinger³

et al. 2017

Toxicology in Vitro

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Acute systemic toxicity testing provides the basis for hazard labeling and risk management of chemicals. A number of international efforts have been directed at identifying non-animal alternatives for in vivo acute systemic toxicity tests. A September 2015 workshop, Alternative Approaches for Identifying Acute Systemic Toxicity: Moving from Research to Regulatory Testing, reviewed the state-of-the-science of non-animal alternatives for this testing and explored ways to facilitate implementation of alternatives. Workshop attendees included representatives from international regulatory agencies, academia, nongovernmental organizations, and industry. Resources identified as necessary for meaningful progress in implementing alternatives included compiling and making available high-quality reference data, training on use and interpretation of in vitro and in silico approaches, and global harmonization of testing requirements. Attendees particularly noted the need to characterize variability in reference data to evaluate new approaches. They also noted the importance of understanding the mechanisms of acute toxicity, which could be facilitated by the development of adverse outcome pathways. Workshop breakout groups explored different approaches to reducing or replacing animal use for acute toxicity testing, with each group crafting a roadmap and strategy to accomplish near-term progress. The workshop steering committee has organized efforts to implement the recommendations of the workshop participants.

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Section: Using Mechanisms and Adverse Outcome Pathways To Integratsupporting

confidence: 63%

Alternative approaches for identifying acute systemic toxicity: Moving from research to regulatory testing

Hamm

Sullivan

Clippinger³

et al. 2017

Toxicology in Vitro

Self Cite

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“…Recently, Bhhatarai et al. ( 2015 ) reported that the data generated in the in vitro MMP assay directly correlated with data obtained in in vivo toxicity studies in fish, Daphnia , and rats dosed by the intravenous route, but not the oral route. Oral administration of the compounds may alter the acute toxicity of compounds in mammals due to the first pass liver effect, bioavailability, and metabolism.…”

Section: Discussionmentioning

confidence: 86%

Comprehensive Analyses and Prioritization of Tox21 10K Chemicals Affecting Mitochondrial Function by in-Depth Mechanistic Studies

Xia

Huang

Shi

et al. 2018

Environ Health Perspect

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Background:A central challenge in toxicity testing is the large number of chemicals in commerce that lack toxicological assessment. In response, the Tox21 program is re-focusing toxicity testing from animal studies to less expensive and higher throughput in vitro methods using target/pathway-specific, mechanism-driven assays.Objectives:Our objective was to use an in-depth mechanistic study approach to prioritize and characterize the chemicals affecting mitochondrial function.Methods:We used a tiered testing approach to prioritize for more extensive testing 622 compounds identified from a primary, quantitative high-throughput screen of 8,300 unique small molecules, including drugs and industrial chemicals, as potential mitochondrial toxicants by their ability to significantly decrease the mitochondrial membrane potential (MMP). Based on results from secondary MMP assays in HepG2 cells and rat hepatocytes, 34 compounds were selected for testing in tertiary assays that included formation of reactive oxygen species (ROS), upregulation of p53 and nuclear erythroid 2-related factor 2/antioxidant response element (Nrf2/ARE), mitochondrial oxygen consumption, cellular Parkin translocation, and larval development and ATP status in the nematode Caenorhabditis elegans.Results:A group of known mitochondrial complex inhibitors (e.g., rotenone) and uncouplers (e.g., chlorfenapyr), as well as potential novel complex inhibitors and uncouplers, were detected. From this study, we identified four not well-characterized potential mitochondrial toxicants (lasalocid, picoxystrobin, pinacyanol, and triclocarban) that merit additional in vivo characterization.Conclusions:The tier-based approach for identifying and mechanistically characterizing mitochondrial toxicants can potentially reduce animal use in toxicological testing. https://doi.org/10.1289/EHP2589

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“…For example, Bhhatarai et al recently reported a modeling study of acute toxicity, which incorporated simulations of absorption and metabolism into the modeling process. 129 Strope et al also reported a modeling study that resulted in an ionization constant (p K a ) model for a set of 32 413 chemicals. 135 The applicability of this model was evaluated by using the p K a predictions to estimate distribution ratio into tissues for 22 compounds with steady-state volume of distribution data.…”

Section: Other Areas Of Computational Toxicology In the Big Data Eramentioning

confidence: 99%

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

Ciallella

Zhu

2019

Chem. Res. Toxicol.

145

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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 mission is the advancement of computational toxicology and artificial intelligence approaches to implementing innovative testing methods. In the current big data era, the terms volume (amount of data), velocity (growth of data), and variety (the diversity of sources) have been used to characterize the currently available chemical, in vitro, and in vivo data for toxicity modeling purposes. Furthermore, as suggested by various scientists, the variability (internal consistency or lack thereof) of publicly available data pools, such as PubChem, also presents significant computational challenges. The development of novel artificial intelligence approaches based on public massive toxicity data is urgently needed to generate new predictive models for chemical toxicity evaluations and make the developed models applicable as alternatives for evaluating untested compounds. In this procedure, traditional approaches (e.g., QSAR) purely based on chemical structures have been replaced by newly designed data-driven and mechanism-driven modeling. The resulting models realize the concept of adverse outcome pathway (AOP), which can not only directly evaluate toxicity potentials of new compounds, but also illustrate relevant toxicity mechanisms. The recent advancement of computational toxicology in the big data era has paved the road to future toxicity testing, which will significantly impact on the public health.

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Acute Toxicity Prediction in Multiple Species by Leveraging Mechanistic ToxCast Mitochondrial Inhibition Data and Simulation of Oral Bioavailability

Cited by 18 publications

References 37 publications

Alternative approaches for identifying acute systemic toxicity: Moving from research to regulatory testing

Alternative approaches for identifying acute systemic toxicity: Moving from research to regulatory testing

Comprehensive Analyses and Prioritization of Tox21 10K Chemicals Affecting Mitochondrial Function by in-Depth Mechanistic Studies

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

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