According to the author's keywords (Figure ), the most recent articles (see color scale) are focused on ML methods such as deep learning. It is also highlighted that the concept of chemical space has had recent applications in Alzheimer's disease and in emerging diseases such as COVID-19. Particularly for COVID-19, chemical space visualization proved to be a fast way to analyze and describe the huge chemical space of known antiviral compounds . For instance, GTM is one of the methods used to represent the chemical space of compounds obtained from medicinal chemistry efforts against coronaviruses (CoVs) . In particular, GTMs helped highlight the structural relationship between antivirals of different categories, predict their polypharmacological profiles, and emphasize frequently encountered chemotypes. Similarly, chemical space concept was very helpful in finding attractive compounds for repositioning and guiding the identification of potent and selective scaffolds with anti-COVID activity . Advances in AI and availability of software libraries have resulted in ML methods, such as deep learning and versatile tools for exploring chemical space for drug discovery applications . Table summarizes the novel approaches using ML methods, some of which have been mentioned previously.