Development of an analytical method to derive hydrophobicity parameters for use as descriptors for the prediction of the environmental and human health risk of chemicals
There is a requirement to assess the safety of chemicals to both 'man' and the environment. Traditionally this was determined through the use of animal testing. However, there is an increased need to develop alternatives to animal testing for the determination of toxicity due to ethical and legislative reasons. One approach to replacing the use of animals is the application of computational methods. These include Quantitative Structure-Activity Relationships ((Q)SARs), which are the formalisation of the relationship of the effects (e.g. toxicity) for a series of chemicals and their physico-chemical and structural properties. Most QSARs for toxicity require knowledge of a chemicals hydrophobicity. Traditionally hydrophobicity has been characterised by the logarithm of the octanol/water partition coefficient (log P). Current experimental and predictive methods are limited in terms of applicability for compounds with extreme log P values, compounds ionised under the conditions of analysis and surface active agents. An alternative technique to assess hydrophobicity is Immobilised Artificial Membrane High Performance Liquid Chromatography (IAM-HPLC). The IAM stationary phase was developed initially to mimic biological membranes more realistically than octanol/water partitioning. This study has collated published literature values for the IAM retention index (kIAM), including details of the experimental procedure, into a database. The database includes 1910 values for 647 compounds. The effect of variability of experimental procedure on reported values was investigated. Key experimental parameters were identified that ensure comparable log kIAM values. An IAM-HPLC method was optimised; the HPLC method covers a range of hydrophobicities (log P of -1.35 to 6.03) and includes both unionised and ionised compounds under the conditions of analysis. Additionally the method has been demonstrated to be robust across system of analysis, column and stationary phase batch. The assessment of robustness increases confidence in the log kIAM (pH 7.4) values for 66 aliphatic and aromatic compounds determined as part of this work. Methods to predict log klAM (pH 7.4) were investigated. Both a fragment and correction factor method, based on theoretical structural features, and a 'classical' descriptor based QSAR approach, was applied to both the experimental log kIAM (pH 7.4) values determined in this work and comparable values collated from the literature. QSARs have been developed using log klAM as a descriptor to predict the ability of a chemical to cross the skin barrier and to predict various acute aquatic toxicity endpoints, using published skin absorption and ecotoxicity data respectively.
GE Environmental Sciences, QD Chemistry, R Medicine (General), RL Dermatology
Networked Digital Library of Theses and Dissertations