By utilising these representations (Table ), a substantial amount of drug exploration has been accomplished thus far. An instance of identifying novel antibiotics was achieved through a deep neural network model, which underwent training utilising an extensive database comprising chemical compounds and their corresponding efficacy against various bacterial strains ( ). The development of a generative tensorial reinforcement learning (GENTRL) model by Insilico Medicine resulted in the rapid identification of new highly effective DDR1 kinase inhibitors ( ). Machine learning techniques have been utilised in several applications, such as exploring potential drugs for Alzheimer's disease ( ). The research on Alzheimer's disease showcased the capacity of machine learning-based virtual screening approaches for drug discovery.