Over the past few decades, computer scientists have developed deep learning tools for a broad variety of applications, including for the analysis of pharmaceutical drugs. Most recently, deep learning models that predict the properties of pharmaceuticals have been trained to analyze and learn molecular representations. Researchers at Tsinghua University, the National University of Singapore, Fudan University's School of Pharmacy, and Zheijang University have recently developed MolMapNet, a new artificial intelligence (AI) tool that can predict the pharmaceutical properties of drugs by analyzing human-knowledge-based molecular representations. This tool, presented in a paper published in Nature Machine Intelligence, can also be used by people with little or no knowledge of computer science, biology or other sciences. "We were aware that pharmaceutical investigations require the learning of many molecular characters, particularly the rich collection of molecular properties (like volume) derived from human knowledge, but these molecular properties are tough to learn by AI (artificial intelligence)," Yu Zong Chen, one of the researchers who carried out the study, told TechXplore.