Hills, E.E.; (2008) The prediction of human oral bioavailability of drugs. Doctoral thesis , University of London.

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Abstract

The aim of this project was to develop a model for prediction of bioavailability of drug compounds from structural features. Literature bioavailability data was gathered for over 700 compounds. This data was evaluated and assigned a quality score. Prodrugs and drugs known to be actively transported were excluded from the dataset. The factors that affect bioavailability include solubility, permeability and first-pass metabolism. Each of these factors was considered. The first stage was to develop a model to predict solubility and to study the effects of pH on solubility. Solubility was measured in water for a set of 99 compounds selected from the bioavailability dataset, using HPLC as the analytical method. Solubility was also measured in simulated gastric fluid, SGF (pH 1.2), and simulated intestinal fluid (fed state and fasted state), FeSSIF and FaSSIF at pH 6.5. An equation for change in solubility with pH was shown to perform quite well. An Abraham equation was developed to account for solubility enhancement due to the presence of micelles in simulated intestinal fluid. Abraham equations were derived for prediction of diffusion in water and in ethanol using literature data. Diffusion in ethanol was predicted best and was used in place of permeability to classify the bioavailability data according to the Biopharmaceutics Classification System. A compound which is highly metabolised will have low bioavailability. Human plasma clearance data was used as a measure of the degree of metabolism of a drug. A molecular fragment-based approach using PLS statistics was used to develop a model of human plasma clearance of drugs for over 400 drugs. The final stage of this work was to develop a model of bioavailability. The best model used PLS statistics and included chain-based molecular fragments in combination with calculated aqueous solubility, diffusion coefficients (in ethanol) and plasma clearance.

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