Cancer novel drugs using machine learning

This work revolves around studying the state of art in this field. It gathers all the information about the drugs discovered and registered with the NIC. The originality of the website lies in integration of heterogeneous biological data and compatibility with the ChEMBL databse. The server accepts any significant biomarkers revealed from the pathological samples of the patient and obtain a variety of trained models with varying accuracies facilitating the user to select the one providing the highest accuracy enabling efficient drug-target interaction.