The future of toxicity testing: a focus on in vitro methods using a quantitative high-throughput screening platform

Shukla, Sunita J.; Huang, Ruili; Austin, Christopher P.; Xia, Menghang

doi:10.1016/j.drudis.2010.07.007

Cited by 249 publications

(186 citation statements)

References 56 publications

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“…The Toxicology in the Twenty-first Century (Tox21) challenge, launched in the United States in 2008, is the largest study of toxic substances to date (Shukla et al, 2010). The Tox21 project is promoted as a collaborative research among the National Institute of Health (NIH), Environmental Protection Agency (EPA), and Food and Drug Administration (FDA), and accords with the Memorandum of Understanding, which outlines the legal requirements of collaboration among U.S. public institutions (http://epa.gov/ncct/Tox21/; Ettlin, 2013;Tice et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

“…Competitors predicted the existence of unpublished activities of various "evaluation set compounds" from the chemical structures and known activities of "training set compounds" extracted from the Tox21 10K library. The competition targets were the 12 proteins/pathways mentioned above, including PPARγ and p53 (Shukla et al, 2010). On a homepage designed for the challenge, the organizers uploaded the chemical structures of approximately 8,000 compounds in the Tox21 10K library as the target data, and their assay results of the proteins/pathways as the training set.…”

Section: Introductionmentioning

confidence: 99%

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Rigorous Selection of Random Forest Models for Identifying Compounds that Activate Toxicity-Related Pathways

Uesawa

2016

Front. Environ. Sci.

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Random forest (RF) is a machine-learning ensemble method with high predictive performance. Majority voting in RF uses the discrimination results in numerous decision trees produced from bootstrapping data. For the same dataset, the bootstrapping process yields different predictive capacities in each generation. As participants in the Toxicology in the Twenty-first Century (Tox21) DATA Challenge 2014, we produced numerous RF models for predicting the structures of compounds that can activate each toxicity-related pathway, and then selected the model with the highest predictive ability. Half of the compounds in the training dataset supplied by the competition organizer were allocated to the validation dataset. The remaining compounds were used in model construction. The charged and uncharged forms of each molecule were calculated using the molecular operating environment (MOE) software. Subsequently, the descriptors were computed using MOE, MarvinView, and Dragon. These combined methods yielded over 4,071 descriptors for model construction. Using these descriptors, pattern recognition analyses were performed by RF implemented in JMP Pro (a statistical software package). A hundred to two hundred RF models were generated for each pathway. The predictive performance of each model was tested against the validation dataset, and the best-performing model was selected. In the competition, the latter model selected a best-performing model from the 50% test set that best predicted the structures of compounds that activate the estrogen receptor ligand-binding domain (ER-LBD).

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Rigorous Selection of Random Forest Models for Identifying Compounds that Activate Toxicity-Related Pathways

Uesawa

2016

Front. Environ. Sci.

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“…Recently, the NTP, the NIH Chemical Genomics Center, and the U.S. Environmental Protection Agency initiated the Tox21 program for the development and validation of in vitro assays through the use of a high-throughput screening (HTS) platform. [11][12][13] Various in vitro approaches have been described in the literature to screen for hepatotoxicity. [14][15][16][17][18] Recently, the advent of quantitative high-throughput screening (qHTS) has enabled researchers to obtain inhibitory concentration at 50% (IC 50 ) values directly from primary ABBREVIATIONS: ATP, adenosine triphosphate; CV, coefficient of variation; CYP, cytochrome P450; DILI, drug-induced liver injury; DMSO, dimethyl sulfoxide; FRD, flying reagent dispenser; HCS, high content screening; HTS, high-throughput screening; IC 50 , inhibitory concentration at 50%; LC/MS/MS, liquid chromatography tandem mass spectrometry; NTP, National Toxicity Program; qHTS, quantitative high-throughput screening; S/B, signal to background; SD, standard deviation; ST, sulfotransferase; UGT, UDP-glucuronosyltransferase; UPLC/MS/MS, ultra performance liquid chromatography tandem mass spectrometry.…”

Section: Introductionmentioning

confidence: 99%

Assessment of Compound Hepatotoxicity Using Human Plateable Cryopreserved Hepatocytes in a 1536-Well-Plate Format

Moeller¹,

Shukla

Xia

2012

ASSAY and Drug Development Technologies

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Hepatotoxicity is a major concern for both drug development and toxicological evaluation of environmental chemicals. The assessment of compound-induced hepatotoxicity has traditionally relied on in vivo testing; however, it is being replaced by human in vitro models due to an emphasis on the reduction of animal testing and species-specific differences. Since most cell lines and hybridomas lack the full complement of enzymes at physiological levels found in the liver, primary hepatocytes are the gold standard to study liver toxicities in vitro due to the retention of most of their in vivo activities. Here, we optimized a cell viability assay using plateable cryopreserved human hepatocytes in a 1536-well-plate format. The assay was validated by deriving inhibitory concentration at 50% values for 12 known compounds, including tamoxifen, staurosporine, and phenylmercuric acetate, with regard to hepatotoxicity and general cytotoxicity using multiple hepatocyte donors. The assay performed well, and the cytotoxicity of these compounds was confirmed in comparison to HepG2 cells. This is the first study to report the reliability of using plateable cryopreserved human hepatocytes for cytotoxicity studies in a 1536-well-plate format. These results suggest that plateable cryopreserved human hepatocytes can be scaled up for screening a large compound library and may be amenable to other hepatocytic assays such as metabolic or drug safety studies.

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“…5,6 Currently, there is no in vitro method that can be used in a high throughput manner to identify kidney toxic agents early in the process before reaching humans. Immortalized kidney epithelial cell lines, derived from human kidney (HK-2), 7 pig kidney (LLC-PK1), or dog kidney (MDCK), 8 frequently used for nephrotoxicity studies, do not fully express all the differentiated functions found in their in vivo counterparts due to loss of polar architecture and changes in drug transporter expression.…”

mentioning

confidence: 99%

A Quantitative Approach to Screen for Nephrotoxic Compounds In Vitro

Adler

Ramm

Hafner

et al. 2016

Journal of the American Society of Nephrology

105

102

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Nephrotoxicity due to drugs and environmental chemicals accounts for significant patient mortality and morbidity, but there is no high throughput in vitro method for predictive nephrotoxicity assessment. We show that primary human proximal tubular epithelial cells (HPTECs) possess characteristics of differentiated epithelial cells rendering them desirable to use in such in vitro systems. To identify a reliable biomarker of nephrotoxicity, we conducted multiplexed gene expression profiling of HPTECs after exposure to six different concentrations of nine human nephrotoxicants. Only overexpression of the gene encoding heme oxygenase-1 (HO-1) significantly correlated with increasing dose for six of the compounds, and significant HO-1 protein deregulation was confirmed with each of the nine nephrotoxicants. Translatability of HO-1 increase across species and platforms was demonstrated by computationally mining two large rat toxicogenomic databases for kidney tubular toxicity and by observing a significant increase in HO-1 after toxicity using an ex vivo three-dimensional microphysiologic system (kidneyon-a-chip). The predictive potential of HO-1 was tested using an additional panel of 39 mechanistically distinct nephrotoxic compounds. Although HO-1 performed better (area under the curve receiver-operator characteristic curve [AUC-ROC]=0.89) than traditional endpoints of cell viability (AUC-ROC for ATP=0.78; AUC-ROC for cell count=0.88), the combination of HO-1 and cell count further improved the predictive ability (AUC-ROC=0.92). We also developed and optimized a homogenous time-resolved fluorescence assay to allow high throughput quantitative screening of nephrotoxic compounds using HO-1 as a sensitive biomarker. This cell-based approach may facilitate rapid assessment of potential nephrotoxic therapeutics and environmental chemicals. Drugs and environmental chemicals, such as aminoglycoside antibiotics, analgesics, chemotherapeutic agents, and heavy metals, as well as endemic toxins like aristolochic acid are a common cause of AKI or CKD. 1,2 Current approaches to conduct safety and risk assessment of compounds rely predominantly on animal studies, and these results are extrapolated to dose effects in humans despite knowledge that the typical responses of animal models and humans can differ greatly. 3 The lack of adequate models to accurately predict human toxicity contributes to an underestimation of the kidney toxic potential of new therapeutic candidates, which also explains why nephrotoxic effects in patients are often only detected during late phase

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The future of toxicity testing: a focus on in vitro methods using a quantitative high-throughput screening platform

Cited by 249 publications

References 56 publications

Rigorous Selection of Random Forest Models for Identifying Compounds that Activate Toxicity-Related Pathways

Rigorous Selection of Random Forest Models for Identifying Compounds that Activate Toxicity-Related Pathways

Assessment of Compound Hepatotoxicity Using Human Plateable Cryopreserved Hepatocytes in a 1536-Well-Plate Format

A Quantitative Approach to Screen for Nephrotoxic Compounds In Vitro

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