In our first article , we have seen that blood-brain barrier (BBB) has a limited permeability for most chemicals and that getting a drug inside the brain, a step key to drug development process, might be tricky. Some drugs can pass through this barrier passively by diffusion and others can only be delivered by specialized proteins named influx transporters. In this second article we are going to get our data ready for Machine Learning models which will predict substrates of

Drug development is a complicated, costly and time-consuming process , where data science and machine learning can bring decisive advantages . For pharmaceutical business, it takes more than ten years and often more than a billion euros to proceed from the first step, target identification, via drug discovery, development and testing, to the final step: drug approval. During this process about 89 % of the candidate molecules fail to become a drug (Kubiniy 2003). Among the