MetaPath: an electronic knowledge base for collating, exchanging and analyzing case studies of xenobiotic metabolism.

The MetaPath knowledge base was developed for the purpose of archiving, sharing and analyzing experimental data on metabolism, metabolic pathways and crucial supporting metadata. The MetaPath system grew out of the need to compile and organize the results of metabolism studies into a systematic database to facilitate data comparisons and evaluations. Specialized MetaPath data evaluation tools facilitate the review of pesticide metabolism data submitted for regulatory risk assessments as well as exchange of results of complex analyses used in regulation and research.

Investigating the relationship between in vitro-in vivo genotoxicity: derivation of mechanistic QSAR models for in vivo liver genotoxicity and in vivo bone marrow micronucleus formation which encompass metabolism.

Strategic testing as part of an integrated testing strategy (ITS) to maximize information and avoid the use of animals where possible is fast becoming the norm with the advent of new legislation such as REACH. Genotoxicity is an area where regulatory testing is clearly defined as part of ITS schemes. Under REACH, the specific information requirements depend on the tonnage manufactured or imported.

Quantitative structure-activity relationship modeling of dermatomyositis activity of drug chemicals.

Dermatomyositis (DM) is an idiopathic inflammatory disorder consisting of skin and skeletal muscle involvement. Some drugs induce DM or dermatomyositis-like syndrome (DM-LS), the others provoke polymoysitis (PM) or cause elevation of serum levels of muscle enzymes (SE) or give muscle damage (M). The unexpected adverse reactions to drugs causing myositis are not a solved contemporary problem.

Predicting the biodegradation products of perfluorinated chemicals using CATABOL.

Perfluorinated chemicals (PFCs) form a special category of organofluorine compounds with particularly useful and unique properties. Their large use over the past decades increased the interest in the study of their environmental fate. Fluorocarbons may have direct or indirect environmental impact through the products of their decomposition in the environment.

Development and validation of an average mammalian estrogen receptor-based QSAR model.

Development and evaluation of quantitative structure activity relationships (QSARs) for predicting estrogen receptor binding from chemical structure requires reliable algorithms for three-dimensional (3D) QSAR analysis and establishment of structurally diverse training sets of chemicals whose modes of action and measures of potency are well defined. One approach to selecting an appropriate training set is to minimize the biological variability in the model development, by using structurally restricted data sets. A second approach is to extend the structural diversity of chemicals at the cost of increased variability of biological assays.