Inspired by ChatGPT’s popularity and wondering if this approach could speed up the drug design process, scientists decided to create their own genAI model. Scientists coded a model to learn a massive dataset of known chemicals, how they bind to target proteins, and the rules and syntax of chemical structure and properties writ large. The end result can generate countless unique molecular structures that follow essential chemical and biological constraints and effectively bind to their targets — promising to vastly accelerate the process of identifying viable drug candidates for a wide range of diseases, at a fraction of the cost.
