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Rosemary Rodford

Publications and source records attributed to Rosemary Rodford.

4 recordsLinked to original sources

Quantitative structure-activity relationships for predicting skin and respiratory sensitization.

Quantitative structure-activity relationships (QSARs) for predicting skin and respiratory sensitization are reviewed. Overall, progress has been hampered by the sparseness of good quality experimental data, a fact that makes it difficult, at this time, to recommend one or two QSARs for predicting skin and respiratory sensitization. Creation of appropriate data sets for uninvestigated classes of chemicals by experimentation should facilitate the development of more robust QSARs for predicting skin and respiratory sensitization. Such QSARs will be valuable in the evaluation of identifiable toxic hazards where dose responses are relevant, as is the case for skin and respiratory sensitization.

Administration, Cutaneous↗

Quantitative structure-activity relationships for predicting skin and eye irritation.

Recent quantitative structure-activity relationships (QSARs) for the prediction of skin and eye irritation were reviewed. The QSARs in these areas are hindered by the lack of quality in vivo data and by a lack of understanding of the mechanisms of action. Creation of appropriate data sets for experimentation would facilitate the development of robust QSARs for predicting skin and eye irritation.

Animals↗

Quantitative structure-activity relationships for predicting percutaneous absorption rates.

Quantitative structure-activity relationships (QSARs) for predicting percutaneous absorption rates were reviewed. Overall progress has been hampered by the sparseness of good quality experimental data. A number of researchers have used the same data set to develop QSARs for predicting percutaneous absorption rates, a fact that makes it difficult, at this time, to recommend one or two QSARs for predicting percutaneous absorption rates. Identification of chemicals within domains of large chemical universes that should be tested to improve QSARs and the subsequent development of experimental percutaneous absorption rates for those chemicals will facilitate the development of more robust QSARs for predicting percutaneous absorption rates.

Absorption↗

Quantitative structure-activity relationships for predicting mutagenicity and carcinogenicity.

Quantitative structure-activity relationships (QSARs) for predicting mutagenicity and carcinogenicity were reviewed. The QSARs for predicting mutagenicity and carcinogenicity have been mostly limited to specific classes of chemicals (e.g., aromatic amines and heteroaromatic nitro chemicals). The motivation to develop QSARs for predicting mutagenicity and carcinogenicity to screen inventories of chemicals has produced four major commercially available computerized systems that are able to predict these endpoints: Deductive estimation of risk from existing knowledge (DEREK) toxicity prediction by komputer assisted technology (TOPKAT), computer automated structure evaluation (CASE), and multiple computer automated structure evaluation (Multicase). A brief overview of these and some other expert systems for predicting mutagenicity and carcinogenicity is provided. The other expert systems for predicting mutagenicity and carcinogenicity include automatic data analysis using pattern recognition techniques (ADAPT), QSAR Expert System (QSAR-ES), OncoLogic computer optimized molecular parametric analysis of chemical toxicity system (COMPACT), and common reactivity pattern (COREPA).

Animals↗