1
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Ta GH, Weng CF, Leong MK. Development of a hierarchical support vector regression-based in silico model for the prediction of the cysteine depletion in DPRA. Toxicology 2024; 503:153739. [PMID: 38307191 DOI: 10.1016/j.tox.2024.153739] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Revised: 01/22/2024] [Accepted: 01/28/2024] [Indexed: 02/04/2024]
Abstract
Topical and transdermal treatments have been dramatically growing recently and it is crucial to consider skin sensitization during the drug discovery and development process for these administration routes. Various tests, including animal and non-animal approaches, have been devised to assess the potential for skin sensitization. Furthermore, numerous in silico models have been created, providing swift and cost-effective alternatives to traditional methods such as in vivo, in vitro, and in chemico methods for categorizing compounds. In this study, a quantitative structure-activity relationship (QSAR) model was developed using the innovative hierarchical support vector regression (HSVR) scheme. The aim was to quantitatively predict the potential for skin sensitization by analyzing the percent of cysteine depletion in Direct Peptide Reactivity Assay (DPRA). The results demonstrated accurate, consistent, and robust predictions in the training set, test set, and outlier set. Consequently, this model can be employed to estimate skin sensitization potential of novel or virtual compounds.
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Affiliation(s)
- Giang H Ta
- Department of Chemistry, National Dong Hwa University, Shoufeng, Hualien 974301, Taiwan
| | - Ching-Feng Weng
- Institute of Respiratory Disease Department of Basic Medical Science Xiamen Medical College, Xiamen 361023, Fujian, China
| | - Max K Leong
- Department of Chemistry, National Dong Hwa University, Shoufeng, Hualien 974301, Taiwan.
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2
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To KT, Strickland J, Reinke E, Borrel A, Truax J, Maldonado H, Allen D, Kleinstreuer N. Computational application of internationally harmonized defined approaches to skin sensitization: DASS App. BMC Bioinformatics 2024; 25:4. [PMID: 38166637 PMCID: PMC10763465 DOI: 10.1186/s12859-023-05617-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Accepted: 12/13/2023] [Indexed: 01/05/2024] Open
Abstract
BACKGROUND Chemically induced skin sensitization, or allergic contact dermatitis, is a common occupational and public health issue. Regulatory authorities require an assessment of potential to cause skin sensitization for many chemical products. Defined approaches for skin sensitization (DASS) identify potential chemical skin sensitizers by integrating data from multiple non-animal tests based on human cells, molecular targets, and computational model predictions using standardized data interpretation procedures. While several DASS are internationally accepted by regulatory agencies, the data interpretation procedures vary in logical complexity, and manual application can be time-consuming or prone to error. RESULTS We developed the DASS App, an open-source web application, to facilitate user application of three regulatory testing strategies for skin sensitization assessment: the Two-out-of-Three (2o3), the Integrated Testing Strategy (ITS), and the Key Event 3/1 Sequential Testing Strategy (KE 3/1 STS) without the need for software downloads or computational expertise. The application supports upload and analysis of user-provided data, includes steps to identify inconsistencies and formatting issues, and provides predictions in a downloadable format. CONCLUSION This open-access web-based implementation of internationally harmonized regulatory guidelines for an important public health endpoint is designed to support broad user uptake and consistent, reproducible application. The DASS App is freely accessible via https://ntp.niehs.nih.gov/go/952311 and all scripts are available on GitHub ( https://github.com/NIEHS/DASS ).
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Affiliation(s)
- Kimberly T To
- Predictive Toxicology and Information Sciences Group, Discovery and Safety Assessment Division, Inotiv, Inc., Morrisville, NC, 27560, USA.
| | - Judy Strickland
- Predictive Toxicology and Information Sciences Group, Discovery and Safety Assessment Division, Inotiv, Inc., Morrisville, NC, 27560, USA
| | - Emily Reinke
- Predictive Toxicology and Information Sciences Group, Discovery and Safety Assessment Division, Inotiv, Inc., Morrisville, NC, 27560, USA
| | - Alexandre Borrel
- Predictive Toxicology and Information Sciences Group, Discovery and Safety Assessment Division, Inotiv, Inc., Morrisville, NC, 27560, USA
| | - Jim Truax
- Predictive Toxicology and Information Sciences Group, Discovery and Safety Assessment Division, Inotiv, Inc., Morrisville, NC, 27560, USA
| | - Heather Maldonado
- Predictive Toxicology and Information Sciences Group, Discovery and Safety Assessment Division, Inotiv, Inc., Morrisville, NC, 27560, USA
| | - Dave Allen
- Predictive Toxicology and Information Sciences Group, Discovery and Safety Assessment Division, Inotiv, Inc., Morrisville, NC, 27560, USA
| | - Nicole Kleinstreuer
- National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods, Division of Translational Toxicology, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, 27709, USA
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3
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Macmillan DS, Chilton ML, Hillegass J. Improvements to in silico skin sensitisation predictions through privacy-preserving data sharing. Regul Toxicol Pharmacol 2022; 137:105292. [PMID: 36400282 DOI: 10.1016/j.yrtph.2022.105292] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2022] [Revised: 11/01/2022] [Accepted: 11/06/2022] [Indexed: 11/17/2022]
Abstract
In silico models are often built solely on publicly available data which may mean that they are less predictive for proprietary chemical space. Data sharing initiatives can improve the performance of such models, but organisations are often unable to share their data due to the need to protect their business interests and maintain the confidentiality of the chemicals in their research and development programmes. In silico models like Derek Nexus, which use expert knowledge to develop structural alerts based on chemical toxicity, can use proprietary data to identify new areas of chemical space and/or refine existing alerts whilst still preserving the privacy of the confidential data. Five hundred and thirty seven proprietary chemicals with skin sensitisation data were shared which led to the implementation of 7 new alerts and 5 modified alerts, with a concomitant 19% increase in sensitivity and 3% increase in specificity of the model.
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Affiliation(s)
- Donna S Macmillan
- Lhasa Limited, Granary Wharf House, 2 Canal Wharf, Leeds, LS11 5PS, UK.
| | - Martyn L Chilton
- Lhasa Limited, Granary Wharf House, 2 Canal Wharf, Leeds, LS11 5PS, UK
| | - Jedd Hillegass
- Bristol Myers Squibb, 1 Squibb Drive, New Brunswick, NJ, 08903, USA
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4
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Macmillan DS, Chilton ML, Gao Y, Kern PS, Schneider SN. How to resolve inconclusive predictions from defined approaches for skin sensitisation in OECD Guideline No. 497. Regul Toxicol Pharmacol 2022; 135:105248. [PMID: 36007801 DOI: 10.1016/j.yrtph.2022.105248] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Revised: 08/02/2022] [Accepted: 08/12/2022] [Indexed: 10/31/2022]
Abstract
In June 2021 the Organisation for Economic Co-operation and Development published Guideline No. 497 on Defined Approaches for Skin Sensitisation (DASS GL). There are two DAs published, known as the 2o3 and the ITS. The 2o3 uses two concordant results from either the DPRA, KeratinoSens™, or the h-CLAT assays to predict hazard (sensitiser/non-sensitiser). The ITS applies a score to results from the DPRA, the h-CLAT and an in silico model to predict United Nations Globally Harmonized System (GHS) sub-categories (1A/1B/Not Classified). The ITS can use Derek Nexus as the in silico model (known as ITSv1) or use OECD QSAR Toolbox (known as ITSv2). As limitations of the individual in chemico/in vitro assays and in silico predictions are carried through to the DAs, inconclusive predictions are possible for chemicals with results in the borderline range, and chemicals with out of domain results. However, these inconclusive predictions can be resolved by applying a weight of evidence approach. Herein, four case studies are presented, each 'inconclusive' for skin sensitisation potential according to both DAs. A weight of evidence approach was applied to each using a robust scientific approach to provide a conclusive prediction, where possible, based on several additional, non-animal lines of evidence.
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Affiliation(s)
- Donna S Macmillan
- Humane Society International, 1255 23rd St. NW, Suite 450. Washington, DC, 20037, USA.
| | - Martyn L Chilton
- Lhasa Limited, Granary Wharf House, 2 Canal Wharf, Leeds, LS11 5PS, UK
| | - Yuan Gao
- Procter & Gamble Technology (Beijing) Co., Ltd, China
| | - Petra S Kern
- Procter & Gamble Services NV, Temselaan 100, B-1853, Strombeek-Bever, Belgium
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5
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Parris P, Whelan G, Burild A, Whritenour J, Bruen U, Bercu J, Callis C, Graham J, Johann E, Griffin T, Kohan M, Martin EA, Masuda-Herrera M, Stanard B, Tien E, Cruz M, Nagao L. Framework for sensitization assessment of extractables and leachables in pharmaceuticals. Crit Rev Toxicol 2022; 52:125-138. [PMID: 35703156 DOI: 10.1080/10408444.2022.2065966] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
During the toxicological assessment of extractables and leachables in drug products, localized hazards such as irritation or sensitization may be identified. Typically, because of the low concentration at which leachables occur in pharmaceuticals, irritation is of minimal concern; therefore, this manuscript focuses on sensitization potential. The primary objective of performing a leachable sensitization assessment is protection against Type IV induction of sensitization, rather than prevention of an elicitation response, as it is not possible to account for the immunological state of every individual. Sensitizers have a wide range of potencies and those which induce sensitization upon exposure at a low concentration (i.e. strong, or extreme sensitizers) pose the highest risk to patients and should be the focus of the risk assessment. The Extractables and Leachables Safety Information Exchange (ELSIE) consortium has reviewed the status of dermal, respiratory, and systemic risk assessment in cosmetic and pharmaceutical industries, and proposes a framework to evaluate the safety of known or potential dermal sensitizers in pharmaceuticals. Due to the lack of specific regulatory guidance on this topic, the science-driven risk-based approach proposed by ELSIE encourages consistency in the toxicological assessment of extractables and leachables to maintain high product quality and ensure patient safety.
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Affiliation(s)
- Patricia Parris
- Pfizer Worldwide Research, Development and Medical, Kent, UK
| | | | - Anders Burild
- Novo Nordisk A/S, Safety Sciences, Imaging and Data Management, Måløv, Denmark
| | | | - Uma Bruen
- Organon USA Inc., Jersey City, NJ, USA
| | - Joel Bercu
- Gilead Sciences Inc., Foster City, CA, USA
| | - Courtney Callis
- Lilly Research Laboratories, Eli Lilly & Company, Indianapolis, IN, USA
| | | | | | - Troy Griffin
- Teva Branded Pharmaceutical Products R&D, West Chester, PA, USA
| | - Martin Kohan
- Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Cambridge, UK
| | - Elizabeth A Martin
- Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Cambridge, UK
| | | | | | | | - Maureen Cruz
- Faegre Drinker Biddle & Reath LLP, Washington, DC, USA
| | - Lee Nagao
- Faegre Drinker Biddle & Reath LLP, Washington, DC, USA
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6
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Graham JC, Trejo-Martin A, Chilton ML, Kostal J, Bercu J, Beutner GL, Bruen US, Dolan DG, Gomez S, Hillegass J, Nicolette J, Schmitz M. An Evaluation of the Occupational Health Hazards of Peptide Couplers. Chem Res Toxicol 2022; 35:1011-1022. [PMID: 35532537 PMCID: PMC9214767 DOI: 10.1021/acs.chemrestox.2c00031] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Peptide couplers (also known as amide bond-forming reagents or coupling reagents) are broadly used in organic chemical syntheses, especially in the pharmaceutical industry. Yet, occupational health hazards associated with this chemical class are largely unexplored, which is disconcerting given the intrinsic reactivity of these compounds. Several case studies involving occupational exposures reported adverse respiratory and dermal health effects, providing initial evidence of chemical sensitization. To address the paucity of toxicological data, a pharmaceutical cross-industry task force was formed to evaluate and assess the potential of these compounds to cause eye and dermal irritation as well as corrosivity and dermal sensitization. The goal of our work was to inform health and safety professionals as well as pharmaceutical and organic chemists of the occupational health hazards associated with this chemical class. To that end, 25 of the most commonly used peptide couplers and five hydrolysis products were selected for in vivo, in vitro, and in silico testing. Our findings confirmed that dermal sensitization is a concern for this chemical class with 21/25 peptide couplers testing positive for dermal sensitization and 15 of these being strong/extreme sensitizers. We also found that dermal corrosion and irritation (8/25) as well as eye irritation (9/25) were health hazards associated with peptide couplers and their hydrolysis products (4/5 were dermal irritants or corrosive and 4/5 were eye irritants). Resulting outcomes were synthesized to inform decision making in peptide coupler selection and enable data-driven hazard communication to workers. The latter includes harmonized hazard classifications, appropriate handling recommendations, and accurate safety data sheets, which support the industrial hygiene hierarchy of control strategies and risk assessment. Our study demonstrates the merits of an integrated, in vivo -in silico analysis, applied here to the skin sensitization endpoint using the Computer-Aided Discovery and REdesign (CADRE) and Derek Nexus programs. We show that experimental data can improve predictive models by filling existing data gaps while, concurrently, providing computational insights into key initiating events and elucidating the chemical structural features contributing to adverse health effects. This interactive, interdisciplinary approach is consistent with Green Chemistry principles that seek to improve the selection and design of less hazardous reagents in industrial processes and applications.
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Affiliation(s)
- Jessica C Graham
- Genentech, Inc., 1 DNA Way, South San Francisco, California 94080, United States
| | | | - Martyn L Chilton
- Lhasa Limited, Granary Wharf House, 2 Canal Wharf, Leeds LS11 5PS, UK
| | - Jakub Kostal
- The George Washington University, Washington, D.C. 20052, United States
| | - Joel Bercu
- Gilead Sciences, Inc., Foster City, California 94404, United States
| | - Gregory L Beutner
- Bristol Myers Squibb, 1 Squibb Drive, New Brunswick, New Jersey 08901, United States
| | - Uma S Bruen
- Organon, Inc., 30 Hudson Street, Jersey City, New Jersey 07302, United States
| | - David G Dolan
- Amgen Inc., One Amgen Center Drive, Thousand Oaks, California 91320-1799, United States
| | - Stephen Gomez
- Theravance Biopharma US, Inc., South San Francisco, California 94080, United States
| | - Jedd Hillegass
- Bristol Myers Squibb, 1 Squibb Drive, New Brunswick, New Jersey 08901, United States
| | - John Nicolette
- AbbVie Inc., 1 North Waukegan Road, North Chicago, Illinois 60064, United States
| | - Matthew Schmitz
- Takeda Pharmaceutical Company Limited, 35 Landsdowne St., Cambridge, Massachusetts 02139, United States
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7
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Ponting DJ, Burns MJ, Foster RS, Hemingway R, Kocks G, MacMillan DS, Shannon-Little AL, Tennant RE, Tidmarsh JR, Yeo DJ. Use of Lhasa Limited Products for the In Silico Prediction of Drug Toxicity. METHODS IN MOLECULAR BIOLOGY (CLIFTON, N.J.) 2022; 2425:435-478. [PMID: 35188642 DOI: 10.1007/978-1-0716-1960-5_17] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Lhasa Limited have had a role in the in silico prediction of drug and other chemical toxicity for over 30 years. This role has always been multifaceted, both as a provider of predictive software such as Derek Nexus, and as an honest broker for the sharing of proprietary chemical and toxicity data. A changing regulatory environment and the drive for the Replacement, Reduction and Refinement (the 3Rs) of animal testing have led both to increased acceptance of in silico predictions and a desire for the sharing of data to reduce duplicate testing. The combination of these factors has led to Lhasa Limited providing a suite of products and coordinating numerous data-sharing consortia that do indeed facilitate a significant reduction in the testing burden that companies would otherwise be laboring under. Many of these products and consortia can be organized into workflows for specific regulatory use cases, and it is these that will be used to frame the narrative in this chapter.
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8
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Ta GH, Weng CF, Leong MK. In silico Prediction of Skin Sensitization: Quo vadis? Front Pharmacol 2021; 12:655771. [PMID: 34017255 PMCID: PMC8129647 DOI: 10.3389/fphar.2021.655771] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Accepted: 04/20/2021] [Indexed: 01/10/2023] Open
Abstract
Skin direct contact with chemical or physical substances is predisposed to allergic contact dermatitis (ACD), producing various allergic reactions, namely rash, blister, or itchy, in the contacted skin area. ACD can be triggered by various extremely complicated adverse outcome pathways (AOPs) remains to be causal for biosafety warrant. As such, commercial products such as ointments or cosmetics can fulfill the topically safe requirements in animal and non-animal models including allergy. Europe, nevertheless, has banned animal tests for the safety evaluations of cosmetic ingredients since 2013, followed by other countries. A variety of non-animal in vitro tests addressing different key events of the AOP, the direct peptide reactivity assay (DPRA), KeratinoSens™, LuSens and human cell line activation test h-CLAT and U-SENS™ have been developed and were adopted in OECD test guideline to identify the skin sensitizers. Other methods, such as the SENS-IS are not yet fully validated and regulatorily accepted. A broad spectrum of in silico models, alternatively, to predict skin sensitization have emerged based on various animal and non-animal data using assorted modeling schemes. In this article, we extensively summarize a number of skin sensitization predictive models that can be used in the biopharmaceutics and cosmeceuticals industries as well as their future perspectives, and the underlined challenges are also discussed.
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Affiliation(s)
- Giang Huong Ta
- Department of Chemistry, National Dong Hwa University, Shoufeng, Taiwan
| | - Ching-Feng Weng
- Department of Basic Medical Science, Institute of Respiratory Disease, Xiamen Medical College, Xiamen, China
| | - Max K. Leong
- Department of Chemistry, National Dong Hwa University, Shoufeng, Taiwan
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9
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Basketter DA, Kimber I, Ezendam J. Predictive Tests for Irritants and Allergens: Human, Animal, and In Vitro Tests. Contact Dermatitis 2021. [DOI: 10.1007/978-3-030-36335-2_13] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
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10
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Chen X, Taguchi T. Enhanced Skin Adhesive Property of Hydrophobically Modified Poly(vinyl alcohol) Films. ACS OMEGA 2020; 5:1519-1527. [PMID: 32010825 PMCID: PMC6990645 DOI: 10.1021/acsomega.9b03305] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/06/2019] [Accepted: 12/18/2019] [Indexed: 05/05/2023]
Abstract
Hydrophobically modified poly(vinyl alcohol) (hm-PVA) films with various alkyl chain lengths were prepared. Their surface/mechanical properties, cytocompatibility, and porcine skin adhesion strength were evaluated. hm-PVAs had 10 °C higher glass transition temperature than poly(vinyl alcohol) (PVA) (33.4 ± 2.5 °C). The water contact angle of the hm-PVA films increased with alkyl chain length and/or hydrophobic group modification ratio. The tensile strength of the hm-PVA films decreased with increasing alkyl chain length and/or hydrophobic group modification ratio. hm-PVA with short chain lengths (4 mol % propanal-modified PVA; 4C3-PVA) had low cytotoxicity compared with long alkyl chain length hm-PVAs (4 mol % hexanal and nonanal-modified PVA; 4C6-PVA and 4C9-PVA). The 4C3-PVA film had the highest porcine skin adhesion strength. Thus, the 4C3-PVA film is promising as an adhesive for wearable medical devices.
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Affiliation(s)
- Xi Chen
- Graduate
School of Pure and Applied Sciences, University
of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8577, Japan
- Biomaterials
Field, Research Center for Functional Materials, National Institute for Materials Science, 1-1 Namiki, Tsukuba, Ibaraki 305-0044, Japan
| | - Tetsushi Taguchi
- Graduate
School of Pure and Applied Sciences, University
of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8577, Japan
- Biomaterials
Field, Research Center for Functional Materials, National Institute for Materials Science, 1-1 Namiki, Tsukuba, Ibaraki 305-0044, Japan
- E-mail: . Phone: +81-29-851-4498. Fax: +81-29-860-4752
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11
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Ecotoxicological QSARs of Personal Care Products and Biocides. METHODS IN PHARMACOLOGY AND TOXICOLOGY 2020. [DOI: 10.1007/978-1-0716-0150-1_16] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
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12
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Rim KT. In silico prediction of toxicity and its applications for chemicals at work. TOXICOLOGY AND ENVIRONMENTAL HEALTH SCIENCES 2020; 12:191-202. [PMID: 32421081 PMCID: PMC7223298 DOI: 10.1007/s13530-020-00056-4] [Citation(s) in RCA: 45] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 04/21/2020] [Indexed: 04/14/2023]
Abstract
OBJECTIVE AND METHODS This study reviewed the concept of in silico prediction of chemical toxicity for prevention of occupational cancer and future prospects in workers' health. In this review, a new approach to determine the credibility of in silico predictions with raw data is explored, and the method of determining the confidence level of evaluation based on the credibility of data is discussed. I searched various papers and books related to the in silico prediction of chemical toxicity and carcinogenicity. The intention was to utilize the most recent reports after 2015 regarding in silico prediction. RESULTS AND CONCLUSION The application of in silico methods is increasing with the prediction of toxic risks to human and the environment. The various toxic effects of industrial chemicals have triggered the recognition of the importance of using a combination of in silico models in the risk assessments. In silico occupational exposure models, industrial accidents, and occupational cancers are effectively managed and chemicals evaluated. It is important to identify and manage hazardous substances proactively through the rigorous evaluation of chemicals.
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Affiliation(s)
- Kyung-Taek Rim
- Chemicals Research Bureau, Occupational Safety and Health Research Institute, Korea Occupational Safety and Health Agency, Daejeon, Korea
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13
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Barentsen HM, Jonis SU, Pelgrom SM, Rijk JC, Westerink WM, Paulussen JJ. REACH alternative testing strategy for skin sensitization in practice: Fact or fiction? Regul Toxicol Pharmacol 2019; 106:292-302. [DOI: 10.1016/j.yrtph.2019.05.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2018] [Revised: 05/15/2019] [Accepted: 05/16/2019] [Indexed: 10/26/2022]
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14
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Mertl E, Riegel E, Glück N, Ettenberger-Bornberg G, Lin G, Auer S, Haller M, Wlodarczyk A, Steurer C, Kirchnawy C, Czerny T. A dual luciferase assay for evaluation of skin sensitizing potential of medical devices. Mol Biol Rep 2019; 46:5089-5102. [DOI: 10.1007/s11033-019-04964-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2019] [Accepted: 07/02/2019] [Indexed: 10/26/2022]
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15
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Predictive Tests for Irritants and Allergens: Human, Animal, and In Vitro Tests. Contact Dermatitis 2019. [DOI: 10.1007/978-3-319-72451-5_13-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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16
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Wilm A, Kühnl J, Kirchmair J. Computational approaches for skin sensitization prediction. Crit Rev Toxicol 2018; 48:738-760. [DOI: 10.1080/10408444.2018.1528207] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Affiliation(s)
- Anke Wilm
- Center for Bioinformatics, Universität Hamburg, Hamburg, Germany
- HITeC e.V, Hamburg, Germany
| | - Jochen Kühnl
- Front End Innovation, Beiersdorf AG, Hamburg, Germany
| | - Johannes Kirchmair
- Center for Bioinformatics, Universität Hamburg, Hamburg, Germany
- Department of Chemistry, University of Bergen, Bergen, Norway
- Computational Biology Unit (CBU), University of Bergen, Bergen, Norway
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17
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Macmillan DS, Chilton ML. A defined approach for predicting skin sensitisation hazard and potency based on the guided integration of in silico, in chemico and in vitro data using exclusion criteria. Regul Toxicol Pharmacol 2018; 101:35-47. [PMID: 30439387 DOI: 10.1016/j.yrtph.2018.11.001] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2018] [Revised: 11/02/2018] [Accepted: 11/06/2018] [Indexed: 10/27/2022]
Abstract
A decision tree-based defined approach (DA) has been designed using exclusion criteria based on applicability domain knowledge of in chemico/in vitro information sources covering key events 1-3 in the skin sensitisation adverse outcome pathway and an in silico tool predicting the adverse outcome (Derek Nexus). The hypothesis is that using exclusion criteria to de-prioritise less applicable assays and/or in silico outcomes produces a rational, transparent, and reliable DA for the prediction of skin sensitisation potential. Five exclusion criteria have been established: Derek Nexus reasoning level, Derek Nexus negative prediction, metabolism, lipophilicity, and lysine-reactivity. These are used to prioritise the most suitable information sources for a given chemical and results from which are used in a '2 out of 3' approach to provide a prediction of hazard. A potency category (and corresponding GHS classification) is then assigned using a k-Nearest Neighbours model containing human and LLNA data. The DA correctly identified the hazard (sensitiser/non-sensitiser) for 85% and 86% of a dataset with reference LLNA and human data. The correct potency category was identified for 59% and 68% of chemicals, and the GHS classification accurately predicted for 73% and 76% with reference LLNA and human data, respectively.
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Affiliation(s)
- Donna S Macmillan
- Lhasa Limited, Granary Wharf House, 2 Canal Wharf, Leeds, LS11 5PS, UK.
| | - Martyn L Chilton
- Lhasa Limited, Granary Wharf House, 2 Canal Wharf, Leeds, LS11 5PS, UK
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18
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Braeuning C, Braeuning A, Mielke H, Holzwarth A, Peiser M. Evaluation and improvement of QSAR predictions of skin sensitization for pesticides. SAR AND QSAR IN ENVIRONMENTAL RESEARCH 2018; 29:823-846. [PMID: 30251555 DOI: 10.1080/1062936x.2018.1518261] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/22/2018] [Indexed: 06/08/2023]
Abstract
In vivo skin sensitization assays have to be provided by applicants to the competent authorities in the European Union for the approval of active substances (AS) in pesticides. This study aimed to test the practicability of in silico predictions for AS by freely available (Q)SAR tools to evaluate their use as a time- and cost-effective alternative to animal testing in the context of the 3R concept. Predictions of skin sensitization for 48 selected sensitizing and non-sensitizing AS by the software programs CAESAR, Toxtree, OECD (Q)SAR Toolbox, CASE Ultra, Leadscope and SciQSAR were collected and compared. Different data evaluation methodologies (score definition, mean, weighted mean, threshold score definition) were applied to optimize the predictions. The calculation methods were internally cross-validated and further validated with an additional validation set of 80 AS. Although the presented calculation methodologies are not suitable as a stand-alone method, this study has shown weaknesses and strengths of some prominent (Q)SAR programs and diverse combinatorial options in the prediction of skin sensitization by pesticidal AS. The present study will help to foster discussions on in silico alternatives to animal testing in the pesticide area.
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Affiliation(s)
- C Braeuning
- a Department of Pesticides Safety
- d Current address: BIMSB/BIH Genomics at Max Delbrück Centre for Molecular Medicine (MDC) , Berlin , Germany
| | | | - H Mielke
- c Department of Exposure , German Federal Institute for Risk Assessment (BfR) , Berlin , Germany
| | - A Holzwarth
- a Department of Pesticides Safety
- e Both authors contributed equally
| | - M Peiser
- a Department of Pesticides Safety
- e Both authors contributed equally
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Chilton ML, Macmillan DS, Steger-Hartmann T, Hillegass J, Bellion P, Vuorinen A, Etter S, Smith BP, White A, Sterchele P, De Smedt A, Glogovac M, Glowienke S, O'Brien D, Parakhia R. Making reliable negative predictions of human skin sensitisation using an in silico fragmentation approach. Regul Toxicol Pharmacol 2018; 95:227-235. [DOI: 10.1016/j.yrtph.2018.03.015] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2018] [Accepted: 03/20/2018] [Indexed: 01/14/2023]
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