Blood Brain Barrier (BBB) is the collection of vessels of blood with special properties of
permeability that allow a limited range of drug and compounds to pass through it. The BBB plays a vital
role in maintaining balance between intracellular and extracellular environment for brain. Brain Capillary
Endothelial Cells (BECs) act as vehicle for transport and the transport mechanisms across BBB
involve active and passive diffusion of compounds. Efficient prediction models of BBB permeability
can be vital at the preliminary stages of drug development. There have been persistent efforts in identifying
the prediction of BBB permeability of compounds employing multiple machine learning methods
in an attempt to minimize the attrition rate of drug candidates taking up preclinical and clinical trials.
However, there is an urgent need to review the progress of such machine learning derived prediction
models in the prediction of BBB permeability. In the current article, we have analyzed the recently developed
prediction model for BBB permeability using machine learning.