This brief offers an introduction to the fascinating new field of quantitative read-across
structure-activity relationships (q-RASAR) as a cheminformatics modeling approach in the
background of quantitative structure-activity relationships (QSAR) and read-across (RA) as data
gap-filling methods. It discusses the genesis and model development of q-RASAR models
demonstrating practical examples. It also showcases successful case studies on the application
of q-RASAR modeling in medicinal chemistry predictive toxicology and materials sciences. The
book also includes the tools used for q-RASAR model development for new users. It is a valuable
resource for researchers and students interested in grasping the development algorithm of
q-RASAR models and their application within specific research domains.
