Biomedical subjects

Andrew P Worth

Publications and source records attributed to Andrew P Worth.

10 recordsLinked to original sources

PubMed2006

Quantitative structure-activity-activity and quantitative structure-activity investigations of human and rodent toxicity.

Acute toxicity in different biological systems, including humans and rodents in vivo, and human and rodent cell lines in vitro, was investigated. The data were taken from the MEIC (Multicentre Evaluation of In Vitro Cytotoxicity) programme. Quantitative structure-activity-activity relationship (QSAAR) models were developed for the in vivo human and rodent toxicity including a combination of toxicity endpoint and structural descriptors as predictor variables. The human peak blood/serum LC(50) concentrations were most strongly related to human liver cell toxicity, while the in vivo oral human lethal doses were most closely related to the in vivo rodent LD(50) values. The QSAARs included structural descriptors encoding electronic/reactivity properties, presence of H-bond donors, compound aromaticity, and size/shape properties. Quantitative structure-activity relationships (QSARs) were derived by using structural descriptors accounting for molecular hydrophobicity, size and shape, and electronic properties. These models have the potential to provide useful insights in the development of non-animal (in vitro and in silico) methods for predicting human and mammalian toxicity.

Animals↗

PubMed2006

Comparison of the applicability domain of a quantitative structure-activity relationship for estrogenicity with a large chemical inventory.

The aim of the present study was to illustrate that it is possible and relatively straightforward to compare the domain of applicability of a quantitative structure-activity relationship (QSAR) model in terms of its physicochemical descriptors with a large inventory of chemicals. A training set of 105 chemicals with data for relative estrogenic gene activation, obtained in a recombinant yeast assay, was used to develop the QSAR. A binary classification model for predicting active versus inactive chemicals was developed using classification tree analysis and two descriptors with a clear physicochemical meaning (octanol-water partition coefficient, or log Kow, and the number of hydrogen bond donors, or n(Hdon)). The model demonstrated a high overall accuracy (90.5%), with a sensitivity of 95.9% and a specificity of 78.1%. The robustness of the model was evaluated using the leave-many-out cross-validation technique, whereas the predictivity was assessed using an artificial external test set composed of 12 compounds. The domain of the QSAR training set was compared with the chemical space covered by the European Inventory of Existing Commercial Chemical Substances (EINECS), as incorporated in the CDB-EC software, in the log Kow / n(Hdon) plane. The results showed that the training set and, therefore, the applicability domain of the QSAR model covers a small part of the physicochemical domain of the inventory, even though a simple method for defining the applicability domain (ranges in the descriptor space) was used. However, a large number of compounds are located within the narrow descriptor window.

Chemical Phenomena↗

PubMed2003

Methods for reliability and uncertainty assessment and for applicability evaluations of classification- and regression-based QSARs.

This article provides an overview of methods for reliability assessment of quantitative structure-activity relationship (QSAR) models in the context of regulatory acceptance of human health and environmental QSARs. Useful diagnostic tools and data analytical approaches are highlighted and exemplified. Particular emphasis is given to the question of how to define the applicability borders of a QSAR and how to estimate parameter and prediction uncertainty. The article ends with a discussion regarding QSAR acceptability criteria. This discussion contains a list of recommended acceptability criteria, and we give reference values for important QSAR performance statistics. Finally, we emphasize that rigorous and independent validation of QSARs is an essential step toward their regulatory acceptance and implementation.

Environmental Exposure↗

PubMed2003

Use of QSARs in international decision-making frameworks to predict ecologic effects and environmental fate of chemical substances.

This article is a review of the use, by regulatory agencies and authorities, of quantitative structure-activity relationships (QSARs) to predict ecologic effects and environmental fate of chemicals. For many years, the U.S. Environmental Protection Agency has been the most prominent regulatory agency using QSARs to predict the ecologic effects and environmental fate of chemicals. However, as increasing numbers of standard QSAR methods are developed and validated to predict ecologic effects and environmental fate of chemicals, it is anticipated that more regulatory agencies and authorities will find them to be acceptable alternatives to chemical testing.

Decision Making, Organizational↗

PubMed2003

Use of QSARs in international decision-making frameworks to predict health effects of chemical substances.

This article is a review of the use of quantitative (and qualitative) structure-activity relationships (QSARs and SARs) by regulatory agencies and authorities to predict acute toxicity, mutagenicity, carcinogenicity, and other health effects. A number of SAR and QSAR applications, by regulatory agencies and authorities, are reviewed. These include the use of simple QSAR analyses, as well as the use of multivariate QSARs, and a number of different expert system approaches.

Animals↗

PubMed2003

Quantitative structure-activity relationships for human health effects: commonalities with other endpoints.

This article describes the use of quantitative structure-activity relationships (QSARs) to predict toxicity endpoints for ecologically relevant and human-surrogate species. The interrelationships between the endpoints, and the possibilities of exploring the commonalities of chemical action from one species to another as well as from one endpoint to another, are evaluated. A number of toxic endpoints are discussed including mutagenicity and carcinogenicity; developmental toxicity (teratogenicity); acute toxicity; skin sensitization; skin, eye, and sensory irritation; and the modeling of membrane permeability. A number of electrophilic molecular substructures have been identified that are common to a number of toxicities. It is postulated that if such a substructure is observed in a molecule, it may exhibit a range of toxicities. Further, there appear to be relationships between the toxicity to ecologically relevant and human-surrogate species, which may allow for appreciation and possible extrapolation in both directions. Overall, however, QSARs are limited by the paucity of available toxicological data and information.

Animals↗

PubMed2002

The principles of validation and the ECVAM validation process.

The validation of a test method is the process by which the relevance and reliability of the method are assessed for a particular purpose. It is an essential stage in the evolution of the method from its development to its acceptance and application for regulatory purposes. The principles according to which alternative tests should be validated have been agreed at an international level, although the actual process by which the validation process is conducted varies between different validation authorities. This paper summarises the principles of alternative test development and validation, and describes how the principles have been applied to the validation of in vitro tests by ECVAM.

Animal Testing Alternatives↗

PubMed2002

ECVAM's activities on computer modelling and integrated testing.

This paper introduces the basic concepts of quantitative structure-activity relationship (QSAR), expert system and integrated testing strategy, and explains how the analogy between QSARs and prediction models leads naturally to criteria for the validation of QSARs. ECVAM's in-house research programme on QSAR modelling and integrated testing is summarised, along with plans for the validation of QSAR models and expert system rulebases at the European Union level.

Animal Testing Alternatives↗

PubMedDate not supplied

Structure-based classification of antibacterial activity.

The aim of this study was to develop a simple quantitative structure-activity relationship (QSAR) for the classification and prediction of antibacterial activity, so as to enable in silico screening. To this end a database of 661 compounds, classified according to whether they had antibacterial activity, and for which a total of 167 physicochemical and structural descriptors were calculated, was analyzed. To identify descriptors that allowed separation of the two classes (i.e. those compounds with and without antibacterial activity), analysis of variance was utilized and models were developed using linear discriminant and binary logistic regression analyses. Model predictivity was assessed and validated by the random removal of 30% of the compounds to form a test set, for which predictions were made from the model. The results of the analyses indicated that six descriptors, accounting for hydrophobicity and inter- and intramolecular hydrogen bonding, provided excellent separation of the data. Logistic regression analysis was shown to model the data slightly more accurately than discriminant analysis.

Anti-Bacterial Agents↗

PubMedDate not supplied

Follow-up to the ECVAM prevalidation study on in vitro tests for acute skin irritation. The European Centre for the Validation of Alternative Methods Skin Irritation Task Force report 2.

The European Centre for the Validation of Alternative Methods (ECVAM) Skin Irritation Task Force was established in 1996, to review the status of the development and validation of alternative tests for skin irritation and corrosion, and to identify appropriate non-animal tests for predicting human skin irritation that were sufficiently well-developed to be prevalidated and validated by ECVAM. The EpiDerm method, based on a reconstituted human skin model, was proposed as being sufficiently well advanced to enter a prevalidation (PV) study. Based on a review of test protocols, prediction models (PMs), and data submitted by test developers on ten specified chemicals, with 20% sodium lauryl sulphate as a reference standard, the task force recommended the inclusion of four other tests: EPISKIN and PREDISKIN, based on reconstituted human epidermis or on human skin; the non-perfused pig-ear test, based on pig skin; and the skin integrity function test (SIFT), with ex vivo mouse skin. The prevalidation study on these methods was funded by ECVAM, and took place during 1999-2000. The outcome of the PV study was that none of the methods was ready to enter a formal validation study, and that the protocols and PMs of the methods had to be improved in order to increase their predictive abilities. Improved protocols and PMs for the EpiDerm and EPISKIN methods, the pig ear test, and the SIFT were presented at an extended Task Force meeting held in May 2001. It was agreed that, in the short term, the performance of the revised and harmonised EpiDerm and EPISKIN methods, as well as the modified SIFT, should be evaluated in a further study with a new set of 20 test chemicals. In addition, it was decided that the SIFT and the pig ear test would be compared to see if common endpoints (transepidermal water loss, methyl green-pyronine stain) could be identified.

Animal Testing Alternatives↗