Machine learning methods in drug delivery

Abstract The machine learning methods have been explored in the drug delivery (pharmaceutics) field in many aspects such as predicting the drug loading in particulate matrices, predicting the permeability enhancement through the body barriers and capturing the stable drug delivery systems through different carriers and matrices. This chapter provides an overview and sheds the light on the different un-supervised and supervised machine learning methods that were used by the drug delivery scientists and the formulators together with their beneficial applications. Exploitation of these methods in the drug delivery field especially with the support from the pharmaceutical industry would lead to huge cuts in the resources expenses and would lead to large savings in efforts and time that are usually exerted in the wet-lab try-and-error experiments.