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In Silico Prediction of Chemical Toxicity for Drug Design Using Machine Learning Methods and Structural Alerts

Hongbin Yang, Lixia Sun, Weihua Li, Guixia Liu, Yun Tang
<span title="2018-02-20">2018</span> <i title="Frontiers Media SA"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/r7gejflxajhbzghowl6qigukjq" style="color: black;">Frontiers in Chemistry</a> </i> &nbsp;
This review article at first simply introduced the computational methods used in prediction of chemical toxicity for drug design, including machine learning methods and structural alerts.  ...  The emphasis of this article was put on the recent progress of predictive models built for various toxicities. Available databases and web servers were also provided.  ...  Acute Oral Toxicity According to the exposure routes of chemicals, acute toxicity can be divided into oral, dermal and inhalation, among which acute oral toxicity is the most widely studied in computational  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3389/fchem.2018.00030">doi:10.3389/fchem.2018.00030</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/29515993">pmid:29515993</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC5826228/">pmcid:PMC5826228</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/krvabposrvf4bagglckqnj2ioe">fatcat:krvabposrvf4bagglckqnj2ioe</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190220112742/http://pdfs.semanticscholar.org/22c9/818043358c26a6b7163e546a6b6b20e1fa67.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/22/c9/22c9818043358c26a6b7163e546a6b6b20e1fa67.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3389/fchem.2018.00030"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> frontiersin.org </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5826228" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

SAR and QSAR modeling of a large collection of LD50 rat acute oral toxicity data

Domenico Gadaleta, Kristijan Vuković, Cosimo Toma, Giovanna J. Lavado, Agnes L. Karmaus, Kamel Mansouri, Nicole C. Kleinstreuer, Emilio Benfenati, Alessandra Roncaglioni
<span title="2019-08-30">2019</span> <i title="Springer Science and Business Media LLC"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/5aubiwi6v5beng6iqzj577kiaa" style="color: black;">Journal of Cheminformatics</a> </i> &nbsp;
The median lethal dose for rodent oral acute toxicity (LD50) is a standard piece of information required to categorize chemicals in terms of the potential hazard posed to human health after acute exposure  ...  for predicting five regulatory relevant acute toxicity endpoints.  ...  Acknowledgements KV acknowledges the Bioinformatics group at the Faculty of Science, University of Zagreb, Croatia for the use of their high-performance computing resources. 1  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1186/s13321-019-0383-2">doi:10.1186/s13321-019-0383-2</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/33430989">pmid:33430989</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/wfea5vtrgfejld3wcydz7sl23y">fatcat:wfea5vtrgfejld3wcydz7sl23y</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200215102017/https://jcheminf.biomedcentral.com/track/pdf/10.1186/s13321-019-0383-2" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/39/47/39473a8a24c030c6f3d57b495024ae32e2688d1e.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1186/s13321-019-0383-2"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> springer.com </button> </a>

Methodology of aiQSAR: a group-specific approach to QSAR modelling

Kristijan Vukovic, Domenico Gadaleta, Emilio Benfenati
<span title="2019-04-03">2019</span> <i title="Springer Nature"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/5aubiwi6v5beng6iqzj577kiaa" style="color: black;">Journal of Cheminformatics</a> </i> &nbsp;
for binary classification and Environmental Protection Agency (EPA) acute rat oral toxicity ranking for multi-class classification.  ...  As part of this method, the applicability domain of each prediction is assessed through the applicability domain measure, calculated on the basis of the fingerprint similarities in each local group of  ...  Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1186/s13321-019-0350-y">doi:10.1186/s13321-019-0350-y</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/30945010">pmid:30945010</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC6446381/">pmcid:PMC6446381</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/35osjmoc2neqrlkedpempu7uka">fatcat:35osjmoc2neqrlkedpempu7uka</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190428190507/https://jcheminf.biomedcentral.com/track/pdf/10.1186/s13321-019-0350-y" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/db/d5/dbd5f432fe4a47b5c103069089e614c62c290ec5.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1186/s13321-019-0350-y"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> springer.com </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6446381" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Machine Learning Based Toxicity Prediction: From Chemical Structural Description to Transcriptome Analysis

Yunyi Wu, Guanyu Wang
<span title="2018-08-10">2018</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/3loumxx7kzamnlu4h6x3xoz6ay" style="color: black;">International Journal of Molecular Sciences</a> </i> &nbsp;
In the era of Big Data and artificial intelligence, toxicity prediction can benefit from machine learning, which has been widely used in many fields such as natural language processing, speech recognition  ...  In this article, we review machine learning methods that have been applied to toxicity prediction, including deep learning, random forests, k-nearest neighbors, and support vector machines.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/ijms19082358">doi:10.3390/ijms19082358</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/30103448">pmid:30103448</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/mjgeejthrzex7kbyxgncnncgla">fatcat:mjgeejthrzex7kbyxgncnncgla</a> </span>
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'In silico' toxicology methods in drug safety assessment
"In silico" metode u toksikologiji za procenu bezbednosti lekova

Danijela Đukić-Ćosić, Katarina Baralić, Dragica Jorgovanović, Katarina Živančević, Dragana Javorac, Nikola Stojilković, Biljana Radović, Đurđica Marić, Marijana Ćurčić, Aleksandra Buha-Đorđević, Zorica Bulat, Evica Antonijević-Miljaković (+1 others)
<span title="">2021</span> <i title="Centre for Evaluation in Education and Science (CEON/CEES)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/urfrf6h47rbwpo7kssiag3abby" style="color: black;">Arhiv za farmaciju</a> </i> &nbsp;
This review will summarize current state-of-the-art scientific data on the use of in silico methods in toxicity testing, taking into account their shortcomings, and highlighting the strategies that should  ...  deliver consistent results, while covering the applications of in silico methods in preclinical trials and drug impurities toxicity testing.  ...  Acknowledgement This work was partially supported by The Ministry of Education, Science and Technological Development of the Republic of Serbia (451-03-9/2021-14/200161).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5937/arhfarm71-32966">doi:10.5937/arhfarm71-32966</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/abfojzhk4fhmzp5yteezhiirwe">fatcat:abfojzhk4fhmzp5yteezhiirwe</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20211204192105/https://scindeks-clanci.ceon.rs/data/pdf/0004-1963/2021/0004-19632104257Q.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/bf/97/bf971f3398094bbd50eb7aa1aa850e37e4277df0.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5937/arhfarm71-32966"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>

In vitro prediction of clinical signs of respiratory toxicity in rats following inhalation exposure

E. Da Silva, C. Hickey, G. Ellis, K.S. Hougaard, J.B. Sørli
<span title="">2021</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/q4vgcqoszvgilfycoxjbnrmceu" style="color: black;">Current Research in Toxicology</a> </i> &nbsp;
Karen Bo Frydendall for help in drawing chemical structures.  ...  Emilie Da Silva is supported by the National Research Center for the Working Environment, and the Technical University of Denmark, Department of Environmental Engineering.  ...  the GHS classes of acute oral toxicity.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.crtox.2021.05.002">doi:10.1016/j.crtox.2021.05.002</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/go432tlspre45j3oeynjvo3v3e">fatcat:go432tlspre45j3oeynjvo3v3e</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210602041314/https://pdf.sciencedirectassets.com/321450/1-s2.0-S2666027X21X00023/1-s2.0-S2666027X21000190/main.pdf?X-Amz-Security-Token=IQoJb3JpZ2luX2VjECMaCXVzLWVhc3QtMSJGMEQCICu8D5ty%2Fk%2B4m6ESRHdNRwVWBBY%2FuiNYH4YumduneVXzAiA93D2hWolnV53l7UDPBxb%2B2Z8lDWylKPsOShiLq6mFyyqDBAjM%2F%2F%2F%2F%2F%2F%2F%2F%2F%2F8BEAQaDDA1OTAwMzU0Njg2NSIMLtIPPt7WLZPIuGY3KtcDir9JweSi0lUASp3eq7ZbEZnAr%2FZbovfzeTkxZshRLSvypyFnLmyV34yY%2BpExZiLq6ytn1ZvIyoLNh99%2FJZMzv%2BAnCTs7kb8EW7NX9ho6cAPbvzhTBJ3xWfw%2BbyEX1ljF4vPPyJswoK9XEuuOTG0rX1TwAQUWwOnzz2RpZytLorfWtsDO9bd6LT6Km6a5GCB%2BkaG0tubgETOE5RjX1WNZ1wphD4KXUqivnK3NXGFR0ldCebf%2F0a%2FMzTD3S9Zdfic64XU64Xc1oUYcno1iQgpCVac9W%2BnEV79yPPh49gcDOBFFe%2FrQPfAWouNVgxP2J2bORZvVEF9xF4pALOal9dbx%2BrgcFcKve0kyIUtkW23Uyxd6qhpQRoQQdlkBd6KphZ74XrtufeVeXK3cs6fXyebJjJL7cH6C0WGsw6TeXywAp1mO02rBE6ypNnjXFDI2oH67XjSywfbH%2FGHBVl8DuXpYRO8Jqn3NbMcIjOXy5PGDJa%2F%2FEj7P1nJLHSp%2B5Y6uR6aRrss%2FjxUvTZtVQeATMVzjRZ98fC2y3nFN9S0LsyIrHXbu7%2FZToxQXqc%2F61DvlYT1E57NxP%2BnYxCOwOAawkBA1iWIf8Rik6aSZ4KQAxd0HbdwAPbS9GIkdMO7b24UGOqYBg745JrFqIn6MkFtXuWTxoSE7%2FmZN2CdJ%2Bgg6BI2hVZbMdSpjAuWg3BmqgkmJy2A%2FsX%2FrqmiND6bEKN17eXXLI2tcSkEZje6Y3epwcq5j%2FGzhlfrujr46CY8l3UK2ZmOimqzdqij6U75OQhvtiQGUSv%2FiBS68%2BaX41mhb3nfhcycMs7a00nxw7UScnpu6Qb9sONZ6qP5j%2B%2B7IbsfLNLp3Pc4rFKvlaw%3D%3D&amp;X-Amz-Algorithm=AWS4-HMAC-SHA256&amp;X-Amz-Date=20210602T041302Z&amp;X-Amz-SignedHeaders=host&amp;X-Amz-Expires=300&amp;X-Amz-Credential=ASIAQ3PHCVTY6KCBYXF5%2F20210602%2Fus-east-1%2Fs3%2Faws4_request&amp;X-Amz-Signature=5d12f2d511b1228b9f30af8f7fe2f453097c8046ea3912d067601212bc653336&amp;hash=f2179b77f7600a1d0527dfa4fb3e7649403734e50ba520b55a333f0451910dc4&amp;host=68042c943591013ac2b2430a89b270f6af2c76d8dfd086a07176afe7c76c2c61&amp;pii=S2666027X21000190&amp;tid=spdf-5401f116-20f2-4566-a771-4688f1039aa3&amp;sid=8e4bb47298cdc94bfd694bd-5682eb6822b6gxrqa&amp;type=client" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/60/a7/60a7d13921bf905d4ef4905d11577c57c12e8e41.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.crtox.2021.05.002"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> elsevier.com </button> </a>

Mapping Mechanistic Pathways of Acute Oral Systemic Toxicity Using Chemical Structure and Bioactivity Measurements

Stephen W. Edwards, Mark Nelms, Virginia K. Hench, Jessica Ponder, Kristie Sullivan
<span title="2022-03-07">2022</span> <i title="Frontiers Media SA"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/eky7yur6q5bopoj7r65pskxlc4" style="color: black;">Frontiers in Toxicology</a> </i> &nbsp;
This study separated 11,992 chemicals with curated rat oral acute toxicity information into clusters of structurally similar compounds.  ...  of an efficient tiered testing strategy that can reduce or eliminate animal testing for acute oral toxicity.  ...  Research supporting the use of existing data and in silico approaches to predict acute oral toxicity of mixtures has been successful as well (Chushak et al., 2021; Hamm et al., 2021) .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3389/ftox.2022.824094">doi:10.3389/ftox.2022.824094</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/35295211">pmid:35295211</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC8915918/">pmcid:PMC8915918</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/q5jtqkplxfcjlpnieiirmscwfq">fatcat:q5jtqkplxfcjlpnieiirmscwfq</a> </span>
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Alternative approaches for identifying acute systemic toxicity: Moving from research to regulatory testing

Jon Hamm, Kristie Sullivan, Amy J. Clippinger, Judy Strickland, Shannon Bell, Barun Bhhatarai, Bas Blaauboer, Warren Casey, David Dorman, Anna Forsby, Natàlia Garcia-Reyero, Sean Gehen (+12 others)
<span title="">2017</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/txvwe36ou5ad5gbtefrkbbzd5m" style="color: black;">Toxicology in Vitro</a> </i> &nbsp;
Acute systemic toxicity testing provides the basis for hazard labeling and risk management of chemicals.  ...  and in silico approaches, and global harmonization of testing requirements.  ...  HHSN273201500010C to ILS in support of NICEATM.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.tiv.2017.01.004">doi:10.1016/j.tiv.2017.01.004</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/28069485">pmid:28069485</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC5479748/">pmcid:PMC5479748</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/wlkjwd336zbhtiv6a3wupw4hui">fatcat:wlkjwd336zbhtiv6a3wupw4hui</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200207225117/http://europepmc.org/backend/ptpmcrender.fcgi?accid=PMC5479748&amp;blobtype=pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/41/73/41735919008541cd1350f24dea42ec9c6b616c3d.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.tiv.2017.01.004"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> elsevier.com </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5479748" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Food irradiation: current status and future prospects [chapter]

P. Loaharanu
<span title="">1995</span> <i title="Springer US"> New Methods of Food Preservation </i> &nbsp;
to replace the Cramer classification scheme with a new TTX assessment scheme incorporating the latest scientific developments in in silico and in vitro toxicology Prediction of acute oral toxicity 1) Need  ...  TOPKAT and MCASE) are useful for predicting acute toxicity in categorical terms (e.g. in terms of GHS classifications).  ...  There is therefore an interest in the development and application of efficient and effective non-animal methods for assessing chemical toxicity, including Quantitative Structure-Activity Relationship (  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-1-4615-2105-1_5">doi:10.1007/978-1-4615-2105-1_5</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/7jsivrenbrfhjk2parum6vwlam">fatcat:7jsivrenbrfhjk2parum6vwlam</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170808191430/http://publications.jrc.ec.europa.eu/repository/bitstream/111111111/16180/1/reqno_jrc63826_eur_24748_final%5b1%5d.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/60/d6/60d61d5e0fcd63fe0bc58ff6f37ec676dba70a62.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-1-4615-2105-1_5"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

Investigating cell type specific mechanisms contributing to acute oral toxicity

Pilar Prieto
<span title="">2018</span> <i title="ALTEX Edition"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/kxjj2pbuo5gjjakyeayxjk47yy" style="color: black;">ALTEX: Alternatives to Animal Experimentation</a> </i> &nbsp;
information could be used to develop more predictive in vitro test methods.  ...  Information on mechanisms of toxicity was collected for 114 out of the 123 oral acutely toxic chemicals (see Methods).  ...  Conflict of interest The authors declare that they have no conflict of interest to disclose.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.14573/altex.1805181">doi:10.14573/altex.1805181</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/30015985">pmid:30015985</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/7g6z6vefdjdrjbhgffxszw227u">fatcat:7g6z6vefdjdrjbhgffxszw227u</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190429055139/https://www.altex.org/index.php/altex/article/download/1008/1233" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/79/25/7925e6d61f3a4a69d75d3f36293aade62cfe0929.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.14573/altex.1805181"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>

Computational determination of toxicity risks associated with a selection of approved drugs having demonstrated activity against COVID-19

Maral Aminpour, Williams Ernesto Miranda Delgado, Soren Wacker, Sergey Noskov, Michael Houghton, D. Lorne J. Tyrrell, Jack A. Tuszynski
<span title="2021-10-21">2021</span> <i title="Springer Science and Business Media LLC"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/i2cgmrb52jgttg4ku6htmgt5im" style="color: black;">BMC Pharmacology and Toxicology</a> </i> &nbsp;
Methods We have incorporated machine learning-based computational tools and in silico models into the drug discovery process to predict Adsorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET  ...  Conclusion In summary, this manuscript aims to provide a potentially useful source of essential knowledge on toxicity assessment of 90 compounds for healthcare practitioners and researchers to find off-label  ...  Acknowledgments Authors would like to acknowledge Philip Winter for his help in ADMET predictor software extraction.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1186/s40360-021-00519-5">doi:10.1186/s40360-021-00519-5</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/34674775">pmid:34674775</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/6dechhvwvraghkzdt2s2sthaf4">fatcat:6dechhvwvraghkzdt2s2sthaf4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20211111171809/https://bmcpharmacoltoxicol.biomedcentral.com/track/pdf/10.1186/s40360-021-00519-5.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/f7/96/f7963daa6e7ccb025eabddb874a64eded00a683b.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1186/s40360-021-00519-5"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> springer.com </button> </a>

Big-data and machine learning to revamp computational toxicology and its use in risk assessment

Thomas Luechtefeld, Craig Rowlands, Thomas Hartung
<span title="">2018</span> <i title="Royal Society of Chemistry (RSC)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/fol63s4syrg5jpl3dky27l2a2a" style="color: black;">Toxicology Research</a> </i> &nbsp;
The creation of large toxicological databases and advances in machine-learning techniques have empowered computational approaches in toxicology.  ...  example of how we overestimate the reproducibility and concordance of animal tests. 33 In 2009, Bulgheroni et al. created a simple model for predicting acute oral toxicity using no observed adverse  ...  of about 550 substances can omit the in vivo acute oral toxicity study by using this adaptation". 35 Our analysis thus directly contributed to animal saving.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1039/c8tx00051d">doi:10.1039/c8tx00051d</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/30310652">pmid:30310652</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC6116175/">pmcid:PMC6116175</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ms7njv5sbnh6dfbv5lhospcowi">fatcat:ms7njv5sbnh6dfbv5lhospcowi</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200305062603/https://kops.uni-konstanz.de/bitstream/handle/123456789/42268/Luechtefeld_2-1ivbsukfdkqc47.pdf;jsessionid=A3B030AEE3FD038B1085B77193A1CE37?sequence=1" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/73/22/732237c4a2b13787c263b73fd3c714dc715d7684.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1039/c8tx00051d"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6116175" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Deep Learning Based Regression and Multi-class Models for Acute Oral Toxicity Prediction with Automatic Chemical Feature Extraction [article]

Youjun Xu, Jianfeng Pei, Luhua Lai
<span title="2017-05-04">2017</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
In this study, we developed acute oral toxicity (AOT) models of compounds using the MGE-CNN architecture as a case study.  ...  Three types of high-level predictive models: regression model (deepAOT-R), multi-classification model (deepAOT-C) and multi-task model (deepAOT-CR) for AOT evaluation were constructed.  ...  Yun Tang, from School of Pharmacy, East China University of Science and Technology for valuable dataset of rat oral LD 50  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1704.04718v3">arXiv:1704.04718v3</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/p4rgqvoo3bgbrclntf4jrcueva">fatcat:p4rgqvoo3bgbrclntf4jrcueva</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200901041319/https://arxiv.org/pdf/1704.04718v3.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/37/a9/37a974b0cd678d67f10e799f36cea9599ccd09b3.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1704.04718v3" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Computational Approaches in Preclinical Studies on Drug Discovery and Development

Fengxu Wu, Yuquan Zhou, Langhui Li, Xianhuan Shen, Ganying Chen, Xiaoqing Wang, Xianyang Liang, Mengyuan Tan, Zunnan Huang
<span title="2020-09-11">2020</span> <i title="Frontiers Media SA"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/r7gejflxajhbzghowl6qigukjq" style="color: black;">Frontiers in Chemistry</a> </i> &nbsp;
Then, we perform a systematic classification and description of the databases and software commonly used for ADMET prediction.  ...  In recent years, with the rapid development of computer science, in silico technology has been widely used to evaluate the relevant properties of drugs in the preclinical stage and has produced many software  ...  This method requires only one reference FIGURE 2 | Classification of ADMET prediction strategies. The ADMET prediction includes the primary in silico approaches and the usage of ADMET software.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3389/fchem.2020.00726">doi:10.3389/fchem.2020.00726</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/33062633">pmid:33062633</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC7517894/">pmcid:PMC7517894</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/eaowpr56dbccbdpovcpm7t23se">fatcat:eaowpr56dbccbdpovcpm7t23se</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200930223638/https://fjfsdata01prod.blob.core.windows.net/articles/files/546712/pubmed-zip/.versions/1/.package-entries/fchem-08-00726/fchem-08-00726.pdf?sv=2018-03-28&amp;sr=b&amp;sig=piKcPIO9bnoJAf%2FLh5u5r3brBFDgmBz%2B74c81F8ODNY%3D&amp;se=2020-09-30T22%3A37%3A08Z&amp;sp=r&amp;rscd=attachment%3B%20filename%2A%3DUTF-8%27%27fchem-08-00726.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/9a/9b/9a9b2c3b3073fd084a653789189ef32fff5862d3.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3389/fchem.2020.00726"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> frontiersin.org </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7517894" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

In silico ADME/T modelling for rational drug design

Yulan Wang, Jing Xing, Yuan Xu, Nannan Zhou, Jianlong Peng, Zhaoping Xiong, Xian Liu, Xiaomin Luo, Cheng Luo, Kaixian Chen, Mingyue Zheng, Hualiang Jiang
<span title="2015-09-02">2015</span> <i title="Cambridge University Press (CUP)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/jns6cvwyffcm3ojmxntl7de3mu" style="color: black;">Quarterly Reviews of Biophysics (print)</a> </i> &nbsp;
However, the effectiveness of these tools is highly dependent on their capacity to cope with needs at different stages, e.g. their use in candidate selection has been limited due to their lack of the required  ...  predictability.  ...  Acknowledgements We gratefully acknowledge the financial support from the National Natural Science Foundation of China (Grants 21210003 and 81230076 to H.J., Grant  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1017/s0033583515000190">doi:10.1017/s0033583515000190</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/26328949">pmid:26328949</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/nnr4kctjq5gbfem7esawtbqqgm">fatcat:nnr4kctjq5gbfem7esawtbqqgm</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190220222835/http://pdfs.semanticscholar.org/2a47/a1dbf8e6ab2c68971f0853a76edd282b2fe8.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/2a/47/2a47a1dbf8e6ab2c68971f0853a76edd282b2fe8.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1017/s0033583515000190"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> cambridge.org </button> </a>
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