• Environmental Mutagens and Carcinogens
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• v.20 no.1
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• pp.21-25
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• 2000

Recently there is increasing interest in the use of structure activity relationships for predicting the biological activity of chemicals. The reasons for the interest include the decrease cost and time per chemical as compared with animal or cell system for identifying toxicological effects of chemicals and the reduction in the use of animals for toxicological testing. This study is to test the validity of the mutagenicity data generated from QSAR (Quantitative Structure Activity Relationship) program. Thirty chemicals, which had been evaluated by Ames test during 1997-1999, were assessed with TOPKAT QSAR mutagenicity prediction module. Among 30chemicals experimented, 28 were negative and 2 were positive for Ames test. On the contrary, 23 chemicals showed the high confidence level indicating high prediction rate in mutagenicity evaluation, and 7 chemicals showed the lsow to moderate confidence level indicating low prediction in mutagenicity evaluation. Overall mutagenicity prediction rate was 77% (23/30). The prediction rates for non-mutagenic chemicals were 79% (22/28) and mutagenic chemicals were 50% (1/2). QSAR could be a useful tool in providing toxicological data for newly introduced chemicals or in furnishing data for MSDS or in determining the dose in toxicity testing for chemicals with no known toxicological data.

• Molecular & Cellular Toxicology
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• v.3 no.3
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• pp.177-184
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• 2007

As a possible feasibility of the extrapolation between in vivo and in vitro systems, we investigated the global gene expression from both mouse liver and mouse hepatic cell line treated with hepatotoxic chemical, acetaminophen (APAP), and compared between in vivo and in vitro genomic profiles. For in vivo study, mice were orally treated with APAP and sacrificed at 6 and 24 h. For in vitro study, APAP were administered to a mouse hepatic cell line, BNL CL.2 and sampling was carried out at 6 and 24 h. Hepatotoxicity was assessed by analyzing hepatic enzymes and histopathological examination (in vivo) or lactate dehydrogenase (LDH) assay and morphological examination (in vitro). Global gene expression was assessed using microarray. In high dose APAPtreated group, there was centrilobular necrosis (in vivo) and cellular toxicity with the elevation of LDH (in vitro) at 24 h. Statistical analysis of global gene expression identified that there were similar numbers of altered genes found between in vivo and in vitro at each time points. Pathway analysis identified glutathione metabolism pathway as common pathways for hepatotoxicty caused by APAP. Our results suggest it may be feasible to develop toxicogenomics biomarkers or profiles by comparing in vivo and in vitro genomic profiles specific to this hepatotoxic chemical for application to prediction of liver toxicity.

• Biomolecules & Therapeutics
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• v.15 no.4
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• pp.252-260
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• 2007

As it is needed to assay possible feasibility of extrapolation between in vivo and in vitro systems and to develop a new in vitro method for toxicity testing, we investigated global gene expression from both animal and cell line treated with thioacetamide (TAA) and compared between in vivo and in vitro genomic profiles. For in vivo study, mice were orally treated with TAA and sacrificed at 6 and 24 h. For in vitro study, TAA was administered to a mouse hepatic cell line, BNL CL.2 and sampling was carried out at 6 and 24 h. Hepatotoxicity was assessed by analyzing hepatic enzymes and histopathological examination (in vivo) or lactate dehydrogenase (LDH) assay and morphological examination (in vitro). Global gene expression was assessed using microarray. In high dose TAA-treated group, there was centrilobular necrosis (in vivo) and cellular toxicity with an elevation of LDH (in vitro) at 24 h. Statistical analysis of global gene expression identified that there were similar numbers of altered genes found between in vivo and in vitro at each time points. Pathway analysis identified several common pathways existed between in vivo and in vitro system such as glutathione metabolism, bile acid biosynthesis, nitrogen metabolism, butanoate metabolism for hepatotoxicty caused by TAA. Our results suggest it may be feasible to develop toxicogenomics biomarkers by comparing in vivo and in vitro genomic profiles specific to TAA for application to prediction of liver toxicity.

• Journal of Environmental Health Sciences
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• v.50 no.2
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• pp.113-124
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• 2024

Background: The increasing need to minimize animal testing has sparked interest in alternative methods with more humane, cost-effective, and time-saving attributes. In particular, in silico-based computational toxicology is gaining prominence. Adverse outcome pathway (AOP) is a biological map depicting toxicological mechanisms, composed of molecular initiating events (MIEs), key events (KEs), and adverse outcomes (AOs). To understand toxicological mechanisms, predictive models are essential for AOP components in computational toxicology, including molecular structures. Objectives: This study reviewed the literature and investigated previous research cases related to AOP and in silico methodologies. We describe the results obtained from the analysis, including predictive techniques and approaches that can be used for future in silico-based alternative methods to animal testing using AOP. Methods: We analyzed in silico methods and databases used in the literature to identify trends in research on in silico prediction models. Results: We reviewed 26 studies related to AOP and in silico methodologies. The ToxCast/Tox21 database was commonly used for toxicity studies, and MIE was the most frequently used predictive factor among the AOP components. Machine learning was most widely used among prediction techniques, and various in silico methods, such as deep learning, molecular docking, and molecular dynamics, were also utilized. Conclusions: We analyzed the current research trends regarding in silico-based alternative methods for animal testing using AOPs. Developing predictive techniques that reflect toxicological mechanisms will be essential to replace animal testing with in silico methods. In the future, since the applicability of various predictive techniques is increasing, it will be necessary to continue monitoring the trend of predictive techniques and in silico-based approaches.

• Toxicological Research
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• v.21 no.1
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• pp.1-14
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• 2005

Transgenic mouse models have been introduced and accepted by regulatory bodies as an alternative to carcinogenicity assay models to predict and evaluate chemical carcinogens. The recent research outcomes in transgenic mouse models have made progressive advances in the understanding of chemical carcinogenesis and the evaluation of potential human carcinogens. However, these models still remain to be insufficient assay systems although the insufficiencies have been recognised and are being resolved. Based on up to date information from literature, this review article intends to understand currently accepted transgenic mouse models, issues arising from study design, interpretation of the study, results of validation project and their cancer prediction rate, and further perspectives of cancer assay models from the regulatory view point.

• Biomolecules & Therapeutics
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• v.15 no.3
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• pp.156-161
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• 2007

Rapid advances in pharmacogenomic research have provided important information to improve drug selection, to maximize drug efficacy, and to minimize drug adverse reaction. The SNPs that are the most abundant type of genetic variants have been proven as valid biomarkers to give information on the prediction of pharmacokinetic/pharmacodynamic properties of drugs based on genotype. In order to elucidate a correlation between SNPs of calcium channel encoding gene and adverse reactions of calcium channel blockers, we investigated SNPs in CACNA1C gene known as a binding site of calcium channel blocker. 96 patients with hypertension who had taken or are taking an antihypertensive drug, 1,4-dihydropyridine (DHP) were included for analysis. These patients were composed of 47 patients with adverse drug reactions (ADR) such as edema from calcium channel blockers and 49 patients without ADR as a control group. The exons encoding the drug binding sites were amplified by PCR using specific primers, and SNPs were analyzed by direct sequencing. We found that there was no SNP in the exons encoding DHP binding site, but four novel SNPs in the exon-intron junction region. However, four novel SNPs were not associated with the ADR of calcium channel blockers. In conclusion, this study showed that ADR from calcium channel blockers may not be caused by SNPs of the binding sites of calcium channel blockers in CACNA1C gene.

• Archives of Pharmacal Research
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• v.27 no.10
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• pp.1009-1015
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• 2004

Quantitative Structure-Resolution Relationship (QSRR) using the Comparative Molecular Field Analysis (CoMFA) software was applied to predict the chromatographic behaviors of chiral drugs with an amine moiety on the chiral cellobiohydrolase (CBH) columns. As a result of the Quantitative CoMFA-Resolution Relationship study, using the partial least square method, prediction of the behavior of drugs with amine moiety upon chiral separation became possible from their three dimensional molecular structures. When a mixed mobile phase of 10 mM aqueous phosphate buffer (pH 7.0) - isopropanol (95 : 5) was employed, the best Quantitative CoMFA-Resolution Relationship, derived from the study, provided a cross-validated $q^2$ = 0.933, a normal $r^2$ = 0.995, while the best Quantitative CoMFA-Separation Factor Relationship, also derived from the study, yielded a cross-validated $q^2$ = 0.939, a normal $r^2$ = 0.991. When all of these results are considered, this QSRR-CoMFA analysis appears to be a very useful tool for the preliminary prediction on the chromatographic behaviors of drugs with an amine moiety inside chiral CBH columns.

• Proceedings of the Korean Society of Applied Pharmacology
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• 1995.10a
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• pp.135-136
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• 1995

Resent advances in computer technology have introduced a sophisticated capability for computing the biological fate of toxicants in a biological system. This methodology, which has drastically altered risk assessment skill in toxicology, is designed using all the mechanistic information, and all claim better accuracy with extrapolating capability Iron animal to people than conventional pharmacokinetic methods. Biologically based mathematical models in which the specific mechanistic steps governing tissue disposition(pharmacokinetics) and toxic action (pharmacodynamics) of chemicals are constructed in quantitative terms by a set of equations loading to prediction of the outcome of specific toxicological experiments by computer simulation. pharmacokinetic and pharmacodynamic models are useful in risk assessment because their mechanistic biological basis permits the high-to-low dose, route to route and interspecies extrapolation of the tissue disposition and toxic action of chemicals.

• Journal of Environmental Health Sciences
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• v.40 no.2
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• pp.105-113
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• 2014

Objectives: It is necessary to apply quantitative structure activity relationship (QSAR) for the various chemicals with insufficient toxicity data that are used in the workplace, based on the precautionary principle. This study aims to find application plan of QSAR software tool for predicting health hazards such as genetic toxicity, and carcinogenicity for some chemicals used in the electronics industries. Methods: Toxicity prediction of 21 chemicals such as 5-aminotetrazole, ethyl lactate, digallium trioxide, etc. used in electronics industries was assessed by Toxicity Prediction by Komputer Assisted Technology (TOPKAT). In order to identify the suitability and reliability of carcinogenicity prediction, 25 chemicals such as 4-aminobiphenyl, ethylene oxide, etc. which are classified as Group 1 carcinogens by the International Agency for Research on Cancer (IARC) were selected. Results: Among 21 chemicals, we obtained prediction results for 5 carcinogens, 8 non-carcinogens and 8 unpredictability chemicals. On the other hand, the carcinogenic potential of 5 carcinogens was found to be low by relevant research testing data and Oncologic TM tool. Seven of the 25 carcinogens (IARC Group 1) were wrongly predicted as non-carcinogens (false negative rate: 36.8%). We confirmed that the prediction error could be improved by combining genetic toxicity information such as mutagenicity. Conclusions: Some compounds, including inorganic chemicals and polymers, were still limited for applying toxicity prediction program. Carcinogenicity prediction may be further improved by conducting cross-validation of various toxicity prediction programs, or application of the theoretical molecular descriptors.

• Toxicological Research
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• v.18 no.4
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• pp.311-324
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• 2002

Toxicokinetic studies are intended to provide critical evaluation of drug disposition at toxico-logical doses and help understand the relationship between blood or tissue levels and the time course of toxic events. Relatively high dose levels wed in toxicokinetics, compared to pharmacokinetics, complicates absorption, protein binding, metabolism and elimination processes. In this mini review, frequently wed toxicokinetic models such as linear compartment models, physiological models, and nonlinear kinetic mod-ec are introduced. In addition, optimization of toxicokinetic studies, their role in the drug development process, and prediction oj human toxicokinetics based on animal data by interspecies scaling are briefly discussed.