In this regard, data fusion methods allow putting multiple data observations or calculations (descriptors) together to increase the consistency and confidence of the information derived from the data . Data fusion was developed initially to improve similarity searching. It is a crucial concept that demonstrates its utility to increase the predictability of drug design models against different endpoints (e.g., properties, bioactivity, biological pathways, -omics relationships, etc.) from a huge data diversity such as structural, physicochemical, spectrometry, bioactivity, transcriptomic, imaging, histological data, etc. .