In Silico Models for Ecotoxicity of Pharmaceuticals

Roy, Kunal; Kar, Supratik

doi:10.1007/978-1-4939-3609-0_12

Cited by 17 publications

(6 citation statements)

References 138 publications

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“…Hence, researchers are devoted to developing alternative methods to conquer these limitations of traditional experimental methods. QSAR (Roy et al, 2015a , b ), Read-across (RA) (Jeliazkova et al, 2010 ), Molecular docking (Yao et al, 2013 ) and Expert systems (Roy and Kar, 2016 ), are deemed faster, cheaper and can manifest more information (Mwense et al, 2004 ). In these developing alternative methods, the QSAR model is one of the most widely used methods in silico .…”

Section: Methods Of Concentration Addition and Independence Actionmentioning

confidence: 99%

Mathematical Modeling Approaches for Assessing the Joint Toxicity of Chemical Mixtures Based on Luminescent Bacteria: A Systematic Review

Wang

Bai

et al. 2020

Front. Microbiol.

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Developments in industrial applications inevitably accelerate the discharge of enormous substances into the environment, whereas multi-component mixtures commonly cause joint toxicity which is distinct from the simple sum of independent effect. Thus, ecotoxicological assessment, by luminescent bioassays has recently brought increasing attention to overcome the environmental risks. Based on the above viewpoint, this review included a brief introduction to the occurrence and characteristics of toxic bioassay based on the luminescent bacteria. In order to assess the environmental risk of mixtures, a series of models for the prediction of the joint effect of multi-component mixtures have been summarized and discussed in-depth. Among them, Quantitative Structure-Activity Relationship (QSAR) method which was widely applied in silico has been described in detail. Furthermore, the reported potential mechanisms of joint toxicity on the luminescent bacteria were also overviewed, including the Trojan-horse type mechanism, funnel hypothesis, and fishing hypothesis. The future perspectives toward the development and application of toxicity assessment based on luminescent bacteria were proposed.

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Section: Methods Of Concentration Addition and Independence Actionmentioning

confidence: 99%

Mathematical Modeling Approaches for Assessing the Joint Toxicity of Chemical Mixtures Based on Luminescent Bacteria: A Systematic Review

Wang

Bai

et al. 2020

Front. Microbiol.

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“…Most promising expert systems for toxicity predictions are the following: AMBIT, AIM, Toxtree, OCED Tool Box, DSSTox, Derek Nexus, Meteor, CASE, HazardExpert, PASS, cat-SAR, Toxmatch, AmbitDiscovery, VEGA, ChemIDplus. The details of each expert system can be found elsewhere [34]. Employing the QSAR equation, a computational chemist can build their own expert system using the following flowchart reported in Figure 5.…”

Section: Types Of Computational Approach For a Mixture’s Toxicity mentioning

confidence: 99%

Exploration of Computational Approaches to Predict the Toxicity of Chemical Mixtures

Kar

Leszczyński

2019

Toxics

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Industrial advances have led to generation of multi-component chemicals, materials and pharmaceuticals which are directly or indirectly affecting the environment. Although toxicity data are available for individual chemicals, generally there is no toxicity data of chemical mixtures. Most importantly, the nature of toxicity of these studied mixtures is completely different to the single components, which makes the toxicity evaluation of mixtures more critical and challenging. Interactions of individual chemicals in a mixture can result in multifaceted and considerable deviations in the apparent properties of its ingredients. It results in synergistic or antagonistic effects as opposed to the ideal case of additive behavior i.e., concentration addition (CA) and independent action (IA). The CA and IA are leading models for the assessment of joint activity supported by pharmacology literature. Animal models for toxicity testing are time- and money-consuming as well as unethical. Thus, computational approaches are already proven efficient alternatives for assessing the toxicity of chemicals by regulatory authorities followed by industries. In silico methods are capable of predicting toxicity, prioritizing chemicals, identifying risk and assessing, followed by managing, the risk. In many cases, the mechanism behind the toxicity from species to species can be understood by in silico methods. Until today most of the computational approaches have been employed for single chemical’s toxicity. Thus, only a handful of works in the literature and methods are available for a mixture’s toxicity prediction employing computational or in silico approaches. Therefore, the present review explains the importance of evaluation of a mixture’s toxicity, the role of computational approaches to assess the toxicity, followed by types of in silico methods. Additionally, successful application of in silico tools in a mixture’s toxicity predictions is explained in detail. Finally, future avenues towards the role and application of computational approaches in a mixture’s toxicity are discussed.

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“…The ingested medicines are eventually released into the environment through bodily discharge substances and end up in larger water bodies either as original drugs or as their metabolites. Another important route of drug exposure to the environment is improper disposal of unused drugs which ultimately end up in the aquatic and soil compartments ( Kar and Leszczynski, 2020 ; Ghosh et al., 2020 ; Roy and Kar, 2016 ). Therefore, in the long term, these COVD-19 pharmaceuticals can be a major source of bio-hazards to the environment.…”

Section: Introductionmentioning

confidence: 99%

Are we ready to combat the ecotoxicity of COVID-19 pharmaceuticals? An in silico aquatic risk assessment

2023

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In Silico Models for Ecotoxicity of Pharmaceuticals

Cited by 17 publications

References 138 publications

Mathematical Modeling Approaches for Assessing the Joint Toxicity of Chemical Mixtures Based on Luminescent Bacteria: A Systematic Review

Mathematical Modeling Approaches for Assessing the Joint Toxicity of Chemical Mixtures Based on Luminescent Bacteria: A Systematic Review

Exploration of Computational Approaches to Predict the Toxicity of Chemical Mixtures

Are we ready to combat the ecotoxicity of COVID-19 pharmaceuticals? An in silico aquatic risk assessment

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