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. 2018 Jul:96:1-17.
doi: 10.1016/j.yrtph.2018.04.014. Epub 2018 Apr 17.

In silico toxicology protocols

Glenn J Myatt  1 , Ernst Ahlberg  2 , Yumi Akahori  3 , David Allen  4 , Alexander Amberg  5 , Lennart T Anger  5 , Aynur Aptula  6 , Scott Auerbach  7 , Lisa Beilke  8 , Phillip Bellion  9 , Romualdo Benigni  10 , Joel Bercu  11 , Ewan D Booth  12 , Dave Bower  13 , Alessandro Brigo  14 , Natalie Burden  15 , Zoryana Cammerer  16 , Mark T D Cronin  17 , Kevin P Cross  13 , Laura Custer  18 , Magdalena Dettwiler  19 , Krista Dobo  20 , Kevin A Ford  21 , Marie C Fortin  22 , Samantha E Gad-McDonald  23 , Nichola Gellatly  15 , Véronique Gervais  24 , Kyle P Glover  25 , Susanne Glowienke  26 , Jacky Van Gompel  27 , Steve Gutsell  6 , Barry Hardy  28 , James S Harvey  29 , Jedd Hillegass  18 , Masamitsu Honma  30 , Jui-Hua Hsieh  31 , Chia-Wen Hsu  32 , Kathy Hughes  33 , Candice Johnson  13 , Robert Jolly  34 , David Jones  35 , Ray Kemper  36 , Michelle O Kenyon  20 , Marlene T Kim  32 , Naomi L Kruhlak  32 , Sunil A Kulkarni  33 , Klaus Kümmerer  37 , Penny Leavitt  18 , Bernhard Majer  38 , Scott Masten  7 , Scott Miller  13 , Janet Moser  39 , Moiz Mumtaz  40 , Wolfgang Muster  14 , Louise Neilson  41 , Tudor I Oprea  42 , Grace Patlewicz  43 , Alexandre Paulino  44 , Elena Lo Piparo  45 , Mark Powley  32 , Donald P Quigley  13 , M Vijayaraj Reddy  46 , Andrea-Nicole Richarz  47 , Patricia Ruiz  40 , Benoit Schilter  45 , Rositsa Serafimova  48 , Wendy Simpson  6 , Lidiya Stavitskaya  32 , Reinhard Stidl  38 , Diana Suarez-Rodriguez  6 , David T Szabo  49 , Andrew Teasdale  50 , Alejandra Trejo-Martin  11 , Jean-Pierre Valentin  51 , Anna Vuorinen  9 , Brian A Wall  52 , Pete Watts  53 , Angela T White  29 , Joerg Wichard  54 , Kristine L Witt  7 , Adam Woolley  55 , David Woolley  55 , Craig Zwickl  56 , Catrin Hasselgren  13
Affiliations

In silico toxicology protocols

Glenn J Myatt et al. Regul Toxicol Pharmacol. 2018 Jul.

Abstract

The present publication surveys several applications of in silico (i.e., computational) toxicology approaches across different industries and institutions. It highlights the need to develop standardized protocols when conducting toxicity-related predictions. This contribution articulates the information needed for protocols to support in silico predictions for major toxicological endpoints of concern (e.g., genetic toxicity, carcinogenicity, acute toxicity, reproductive toxicity, developmental toxicity) across several industries and regulatory bodies. Such novel in silico toxicology (IST) protocols, when fully developed and implemented, will ensure in silico toxicological assessments are performed and evaluated in a consistent, reproducible, and well-documented manner across industries and regulatory bodies to support wider uptake and acceptance of the approaches. The development of IST protocols is an initiative developed through a collaboration among an international consortium to reflect the state-of-the-art in in silico toxicology for hazard identification and characterization. A general outline for describing the development of such protocols is included and it is based on in silico predictions and/or available experimental data for a defined series of relevant toxicological effects or mechanisms. The publication presents a novel approach for determining the reliability of in silico predictions alongside experimental data. In addition, we discuss how to determine the level of confidence in the assessment based on the relevance and reliability of the information.

Keywords: Computational toxicology; Expert alert; Expert review; In silico; In silico toxicology; Predictive toxicology; QSAR.

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Figures

Figure 1
Figure 1
Overview of the IST protocol framework, showing how experimental data or in silico model(s) for each defined toxicological effect/mechanism are assessed and used to support a hazard assessment. (Note Effect/Mechanism N is used to illustrate that there can be any number of effects/mechanisms in each protocol) * From the literature, database or study report
Figure 2
Figure 2
Reliability of toxicity assessments based on computational models and experimental data a. Read-across performed according to the RAAF or similar b. Expert review resulting in increased confidence c. 2+ concurring results from different methodologies or QSAR descriptor sets or training sets d. Based on the selection criteria provided in Section 2.3.2
Figure 3
Figure 3
Determining the bacterial gene mutation assessment and reliability score for two concurring in silico results with expert review
Figure 4
Figure 4
Determining the bacterial gene mutation assessment and reliability score for two concurring in silico results with no expert review
Figure 5
Figure 5
Determining the bacterial gene mutation assessment and reliability score where there is no experimental data available and conflicting in silico results
Figure 6
Figure 6
Hazard assessment framework * From the literature, database or study report ** Function of the associated reliability, relevance and completeness
Figure 7
Figure 7
Summary of the IST protocol process * Based on rules/principles outlined in the IST protocols, including an expert review if warranted
See this image and copyright information in PMC

References

    1. Alves V, Muratov E, Capuzzi S, Politi R, Low Y, Braga R, Zakharov AV, Sedykh A, Mokshyna E, Farag S, Andrade C, Kuz’min D, Fourches D, Tropsha A. Alarms about structural alerts. Green Chem. 2016;18(16):4348–4360. doi: 10.1039/C6GC01492E. - DOI - PMC - PubMed
    1. Amaral RTD, Ansell J, Aptula N, Ashikaga T, Chaudhry Q, Hirose A, Jaworska J, Kojima H, Lafranconi M, Matthews E, Milstein S, Roesler C, Vaillancourt E, Verma R, Worth A, Yourick J. Report for the International Cooperation on Cosmetics Regulation. Silico Approaches for Safety Assessment of Cosmetic Ingredients. 2014 https://www.pharmamedtechbi.com/~/media/Supporting%20Documents/The%20Ros....
    1. Amaral R, Amores Da Silva P, Ansell J, Boisleve F, Dent M, Hatao M, Hirose A, Kasai Y, Kojima H, Kern P, Kreiling R, Milstein S, Oliveira J, Richarz A, Taalman R, Vaillancourt E, Verma R, Vieira NC, Weiss C. Report for the International Cooperation on Cosmetics Regulation, Joint Regulators-Industry Working Group: Integrated Strategies for Safety Assessments of Cosmetic Ingredients - Part I. 2017 http://www.iccr-cosmetics.org/files/4715/0824/0761/ICCR-11_JWG_Integrate....
    1. Amberg A, Harvey JS, Czich A, Spirkl H-P, Robinson S, White A, Elder DP. Do Carboxylic/Sulfonic acid halides really present a mutagenic and carcinogenic risk as impurities in final drug products? Org Process Res Dev. 2015;19:1495–506. doi: 10.1021/acs.oprd.5b00106. - DOI
    1. Amberg A, Beilke L, Bercu J, Bower D, Brigo A, Cross KP, Custer L, Dobo K, Dowdy E, Ford KA, Glowienke S, Gompel JV, Harvey J, Hasselgren C, Honma M, Jolly R, Kemper R, Kenyon M, Kruhlak N, Leavitt P, Miller S, Muster W, Nicolette J, Plaper A, Powley M, Quigley DP, Reddy MV, Spirkl HP, Stavitskaya L, Teasdale A, Weiner S, Welch DS, White A, Wichard J, Myatt GJ. Principles and procedures for implementation of ICH M7 recommended (Q)SAR analyses. Regulatory Toxicology and Pharmacology. 2016;77:13–24. doi: 10.1016//j.yrtph.2016.02.004. - DOI - PubMed