Biomedical subjects

G Patlewicz

Publications and source records attributed to G Patlewicz.

3 recordsLinked to original sources

PubMed2006

Validation of counter propagation neural network models for predictive toxicology according to the OECD principles: a case study.

The OECD has proposed five principles for validation of QSAR models used for regulatory purposes. Here we present a case study investigating how these principles can be applied to models based on Kohonen and counter propagation neural networks. The study is based on a counter propagation network model that has been built using toxicity data in fish fathead minnow for 541 compounds. The study demonstrates that most, if not all, of the OECD criteria may be met when modeling using this neural network approach.

Animal Use Alternatives↗

PubMed2002

Mechanism based structure-activity relationships for skin sensitisation--the carbonyl group domain.

The biological activity of skin-sensitising chemicals is related to their ability to react either directly or after metabolic activity with appropriate skin proteins. For direct-acting electrophilic compounds, this ability can be modelled by the Relative Alkylation Index (RAI) by a combination of electrophilicity and hydrophobicity parameters. Several SARs based on this approach are reported. In this present work, electrophilicity parameters based on Taft substituent constants are used together with Leo and Hansch log P fragment values to calculate RAI values for hard electrophiles having a reactive carbonyl group. These are then applied to analysis of sensitisation data obtained in the murine Local Lymph Node Assay (LLNA) for two series of diketones as well as a homologous series of alpha, beta-unsaturated aldehydes. The sensitisation potentials of these reactive electrophiles show good correlations with the RAI. These findings re-affirm the view that physicochemical parameters are the key to eliciting the relationship between chemical structure and a toxic endpoint. They provide further evidence of the value of SAR studies in identifying mechanisms of sensitisation and aiding risk assessments without the need for extensive animal testing.

Aldehydes↗

PubMed2001

Skin-sensitization structure-activity relationships for aldehydes.

A selection of 17 aldehydes (13 sensitizing and 4 non-sensitizing), all of which possessed a benzene ring, were evaluated using structure-activity relationships (SARs). The sensitizing compounds were classified as strong, moderate or weak skin sensitizers on the basis of in vivo data. The aldehydes were grouped into 4 distinct subcategories of functionally related aldehydes that were termed aryl-substituted aliphatic, aryl, aryl with special features (that can undergo metabolism) and alpha,beta-unsaturated aldehydes. It was observed that a structure-activity relationship could be derived for a subset of aldehydes that could react via the same chemical mechanism. This further supports the view that applying knowledge on reaction mechanisms to develop SAR models can provide a more accurate means of investigating and predicting the sensitization potential of structurally and functionally related chemicals.

Aldehydes↗