Mechanism of Action (MoA) Prediction Kaggle Competition
Drugs research is rapidly evolving and latest progress is partially thanks to the introduction of Machine Learning tools. A variety of machine learning methods such as naive Bayesian, support vector machine and, more recently, deep neural networks are demonstrating their usefulness in drug discovery and development. The aim of this paper is to propose various Machine Learning algorithms in order to predict the biological activity of a molecule, which is referred to as mechanismof action, or MoA for short. The model selection has been carried out through a online public competition that elected the best performing models for the given dataset. We describe here the models, based on the Neural Network framework, that we utilized and implemented during the challenge and that made us achieve the top 2% of the final leaderboard, with a position of 72 over 4373 teams.