When providing suitable and comprehensive data we can utilize LLMs in many areas that advance the DD process, such as de novo drug design , Drug-Target Interaction (DTI) prediction , Masked Language Models (MLMs) , Variational Auto-Encoders (VAEs) , binding affinity prediction, drug repurposing , molecular optimization , compound activity prediction , contrastive learning for DTI prediction , and other miscellaneous models.