Predicting chemical toxicity and fate

Cover of: Predicting chemical toxicity and fate |

Published by CRC Press in Boca Raton, Fla .

Written in English

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Subjects:

  • Molecular toxicology,
  • Toxicological chemistry,
  • QSAR (Biochemistry)

Edition Notes

Includes bibliographical references and index

Book details

Statement[edited by] Mark T.D. Cronin and David J. Livingstone
ContributionsCronin, Mark T.D, Livingstone, D.
Classifications
LC ClassificationsRA1220.3 .P74 2004
The Physical Object
Pagination445 p. :
Number of Pages445
ID Numbers
Open LibraryOL17129301M
ISBN 100415271800
LC Control Number2004043999

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Predicting Chemical Toxicity and Fate provides a comprehensive explanation of the state-of-the-art methods that are available to predict the effects of chemicals on humans and the environment. It describes the use of predictive methods to estimate the physiochemical properties, biological activities, and fate of : Hardcover.

Predicting Chemical Toxicity and Fate - CRC Press Book Quantitative Structure-Activity Relationships (QSARs) are increasingly used to predict the harmful effects of chemicals to humans and the environment.

Predicting Chemical Toxicity and Fate provides a comprehensive explanation of the state-of-the-art methods that are available to predict the effects of chemicals on humans and the environment. It describes the use of predictive methods to estimate the physiochemical properties, biological activities, and fate of chemicals.

Predicting Chemical Toxicity and Fate provides a comprehensive explanation of the state-of-the-art methods that are available to predict the effects of chemicals on humans and the environment. It describes the use of predictive methods to estimate the physiochemical properties, biological activities, and fate of by:   Predicting Chemical Toxicity and Fate provides a comprehensive explanation of the state-of-the-art methods that are available to predict the effects of chemicals on humans and the environment.

It describes the use of predictive methods to estimate the physiochemical properties, biological activities, and fate of chemicals.

Predicting chemical toxicity and fate in humans and the environment --an introduction / Mark T.D. Cronin --Ch. Toxicity data sources / Klaus L.E.

Kaiser --Ch. Calculation of physicochemical properties / Mark T.D. Cronin and David J. Livingstone --Ch. Predicting Chemical Toxicity and Fate Quantitative Structure-Activity Relationships (QSARs) are increasingly used to predict the harmful effects of chemicals to humans and the environment.

The increased use of these methods in a variety of areas (academic, industrial, regulatory) results from a realization that very little toxicological or fate data is available on the vast amount of. Analysis of the Relationship between Different Chemical Toxicity Effects.

In the Accelrys Toxicity Database, there are 3, compounds with more than two types of toxicity effects and 3, compounds with exact two effects (refer to Figure 1). We analyzed the number of common compounds belonging to two categories, Cited by: and accumulate the chemical can magnify the source emission.

The actual fate of a chemical depends on the chemical s use pa ttern and physical-chemical properties, combined with the characteristics of the environment to which it is released. A Textbook of Modern Toxicology, Third Edition, edited by. The processes by which chemicals reach sites of toxic action are the subject of this book, and are a fundamental consideration in ecotoxi­ cology.

When a chemical enters the environment e.g. via a spillage or in an effluent, it is potentially subject to a wide variety of processes which may eliminate. The increased use of these methods in a variety of areas (academic, industrial, regulatory) results from a realization that very little toxicological or fate data is available on the vast amount of chemicals to which humans and the environment are ting Chemical Toxicity and Fate provides a comprehensive explanation of the state-of-the-art methods that are available to predict the effects of.

The physicochemical properties of interest to chemical alternatives assessment can be used to identify physical hazards and to understand or predict a chemical's environmental fate, human toxicity, or ecotoxicity (see Figure ).

The committee cautions that given the active research in the field and the potential for special case concerns to Cited by: 1. of environmental toxicity and fate through the use of quantitative structure-activity relationships (QSARs). This paper examines the use of QSARs in this conte : John Dearden.

This book discusses the use of Quantitative Structure-Activity Relationships (QSARs) to predict the toxicity and fate of chemicals both to man and in the environment, and provides a comprehensive explanation of the available predictive methods to estimate the physiochemical properties, biological activities, and fate of chemicals.

The book will provide concise practical guidance for those wishing to apply these methods (in risk / hazard assessment) and will be illustrated with case studies.

Chemical Toxicity Prediction is the first book that addresses the concept of category formation and read-across for toxicity Cited by: 9. Predicting Chemical Toxicology and Fate Resource Type: document --> technical as well as the appropriate use of statistical techniques Illustrates how QSARs and computational methods may predict human health endpoints, including the development of models for mutagenicity and carcinogenicity in addition to pharmacokinetic and metabolic.

There are little available toxicity data on the vast majority of chemicals in commerce. High-throughput screening (HTS) studies, such as those being carried out by the U.S. Environmental Protection Agency (EPA) ToxCast program in partnership with the federal Tox21 research program, can generate biological data to inform models for predicting potential by: This new edition of the Handbook of Physical-Chemical Properties and Environmental Fate for Organic Chemicals is a comprehensive series in four volumes that serves as a reference source for environmentally relevant physical-chemical property data of numerous groups of chemical substances.

The second part of the book discusses various factors that affect transport, transformation, ultimate distribution, and accumulation of chemicals in the aquatic environment, along with the use of modelling to predict fate.; The final section of the book reviews types of effects or endpoints evaluated in field studies and the use of structure 4/5(1).

At several points in this process, it is critical to accurately model the fate of chemical stressors and predict toxicity pathways. For example, one must model the fate and transport of a chemical after it is released into the environment to determine the level of exposure to organisms of concern.

State of the art on prediction methods of toxicity and fate of chemical substances both to man and in the environment with a strong focus on Quantitative Structure–Activity Relationships (QSARs).

Derelanko MJ, Hollinger MA () Handbook of Toxicology, 2nd Edition. Combes RD, Rodford R. The use of expert systems for toxicity prediction—illustrated with reference to the DEREK program.

In: Cronin M, Livingstone D, eds. Predicting Chemical Toxicity and Fate. Boca Raton: CRC Press, – Google ScholarCited by: Predicting chemical toxicity and fate / [edited by] Mark T.D.

Cronin, David J. Livingstone. RA P74 Toxicogenomics and proteomics / edited by James J. Valdes and Jennifer W. Sekowski. Arguably the first book to clearly link ecotoxicology and classic human toxicology, Mixture Toxicity: Linking Approaches from Ecological and Human Toxicology incorporates extensive reviews of.

In Silico methods to predict toxicity have become increasingly important recently, particularly in light of European legislation such as REACH and the Cosmetics Regulation. They are also being used extensively worldwide e.g. in the USA, Canada, Japan and Australia.

In assessing the risk that a chemical may pose to human health or to the environment, focus is now being directed towards. A quantitative structure toxicity relationship (QSTR) has been derived for a diverse set of industrially important aromatic solvents.

Toxicity was expressed as the 50% growth impairment concentration (ICG50) for the ciliated protozoa Tetrahymena and spans the range − to log units.

Molecular descriptors that encode topological, geometrical, electronic, and hybrid geometrical Cited by: Predicting the Toxicities of Chemicals to Aquatic Animal Species Dale Hoff4 Wade Lehmann1 Anita Pease2 Sandy Raimondo3 Chris Russom4 Tom Steeger2 U.S. Environmental Protection Agency 1 Office of Water, Washington, DC 2 Office of Pesticide Programs, Washington, DC 3 Office of Research and Development, Gulf Ecology Division 4.

SoilPlusVeg: An integrated air-plant-litter-soil model to predict organic chemical fate and recycling in forests. Similarly, vegetation concentrations of toxic chemical can vary in time, possibly showing unexpected behaviours: after an initial phase of accumulation, concentration in leaves can respond dynamically to air concentration Cited by:   Purchase Modeling the Fate and Effect of the Toxic Substances in the Environment, Volume 6 - 1st Edition.

Print Book & E-Book. ISBNJournal of chemical information and modeling 8 Journal of cheminformatics 7 Regulatory toxicology and pharmacology 5 Bioinformatics 5 Nucleic acids research 3 PLoS one 3 BMC bioinformatics 2 PLoS computational biology 2 Scientific reports 2 In silico biology 2 Chemical biology & drug design 2 SAR and QSAR in environmental research 2 Organic.

Chemical Toxicity Prediction is the first book that addresses the concept of category formation and read-across for toxicity prediction specifically. This topic has really taken off in the past few years due to concerns over dealing with the REACH legislation and also due to.

Prediction of Environmental Toxicity and Fate Using Quantitative Structure-Activity Relationships (QSARs) An appropriate QSAR can then be selected in order to predict the toxicity of a given chemical. There are also some expert systems available for toxicity prediction.

One of the chief alternatives to animal testing for toxicity is the. Payne M () Computer-based methods for the prediction of chemical metabolism and biotransformation within biological organisms.

In: Cronin MTD, Livingstone DJ (eds) Predicting chemical toxicity and fate. CRC Press, Boca Raton Google ScholarCited by: In silico prediction software for toxicity, metabolic fate and chemical degradation of chemicals; Chemical database software for chemical toxicity information management; Software for the calculation of purge factors; To see a list of our current member organisation, click here.

Toxicity prediction is very important to public health. Among its many applications, toxicity prediction is essential to reduce the cost and labor of a drug’s preclinical and clinical trials, because a lot of drug evaluations (cellular, animal, and clinical) can be spared due to the predicted toxicity.

In the era of Big Data and artificial intelligence, toxicity prediction can benefit from Cited by: Roberts, ) in the last five years, chemical reactivity models have been reported since the s (Landsteiner & Jacobs, ). The use of in chemicomethods for toxicity prediction is based on the assumption that chemical reactivity and toxicity are proportionally related, i.e.

the most reactive chemical will be the most by: 4. Models and tools developed by EPA to assess hazard under TSCA. Ecological Structure-Activity Relationships Program (ECOSAR): Uses quantitative structure-activity relationships (QSAR) to predict the toxicity of untested chemicals based on their structural similarity to chemicals for which aquatic studies are available.

Predictions are based on a library of class-based QSARs within the program. Application of Modern Toxicology Approaches for Predicting Acute Toxicity for Chemical Defense reviews the current state of computational and high-throughput approaches for predicting acute toxicity and suggests methods for integrating data and predictions.

This report concludes with lessons learned from current high-throughput screening. Appendix B Available Data or Databases.

There are many sources of acute-toxicity data. They include peer-reviewed literature and secondary sources, such as The Merck Index (O’Neil ). Several acute-toxicity databases can be easily searched by using chemical name, CAS Registry number, chemical structure, and other identifiers, and some can also be searched on the basis of the type of study.

The CompTox Chemicals Dashboard is a freely accessible online database created and maintained by the U.S. Environmental Protection Agency (EPA). The database provides access to multiple types of data including physicochemical properties, environmental fate and transport, exposure, usage, in vivo toxicity, and in vitro bioassay.

EPA and other scientists use the data and models contained within Research center: Environmental Protection Agency. The aim of this article is to review the worldwide regulatory use of QSARs for predicting the ecologic effects and environmental fate of chemical substances (the regulatory use of QSARs for predicting human health effects forms the basis of a second review; Cronin et al.

).CAFE has two major components: the Fate module, which predicts how a contaminant will behave in the environment, and the Effects module, which determines the chemical’s potential toxicity to different species. In the Fate module, CAFE contains data, such as chemical properties, useful in understanding and predicting chemical behavior in.EPA//R/ June PB STATISTICAL APPROACH TO PREDICTING CHRONIC TOXICITY OF CHEMICALS TO FISHES FROM ACUTE TOXICITY TEST DATA by Foster L.

Mayer U.S. Environmental Protection Agency Environmental Research Laboratory Sabine Island Gulf Breeze, FL Gary F. Krause Mark R. Ellersieck Gunhee Lee University of Missouri Agricultural Experimental .

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