Abstract
Treatment of ocular disorders is a challenge due to the difficulty of delivering drugs to the target tissues within the eye at sufficient concentrations to produce a therapeutic effect. The cornea and the blood-retinal barrier, comprising of the retinal pigment epithelium and the retinal capillaries, are the main barriers for delivering drugs to treat diseases in the anterior and posterior parts of the eye, respectively. The eye has a rich blood supply and relatively small mass, and drugs can distribute from the systemic blood circulation to the choroid through the fenestrated choroidal blood vessels, but further permeation into the eye is limited by the blood-retinal barrier. Computational prediction of the ocular pharmacokinetics of drugs can help improve drug delivery and predict ocular adverse effects resulting from ocular or systemic drugs. Computational models predicting ocular adverse effects of drugs are still scarce, even though prediction of eye irritation and corrosion of chemicals has been well studied as a consequence of recent European Union legislation. Predictive modeling of adverse effects suffers from the wide distribution of data resources, but databases that integrate data on adverse effects, drugs, targets and other related biological data from different sources offer improved prospects for predictive modeling.
Keywords: Cornea, melanin, QSPR, RPE, transporters, vitreous, database, ADME-T, adverse effects, computational modelling and data mining.
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