Target identification is the research stage where scientists determine which biological molecule, pathway, or cell process a therapy should act on. In drug discovery, the "target" is usually a protein, receptor, enzyme, or gene-linked mechanism that appears to drive a disease. The goal is not to find a drug yet, but to choose the right problem to attack.
This step matters because a well-chosen target can make downstream screening, optimization, and testing far more efficient, while a poor target can waste years of work. Researchers use genetics, omics data, disease models, and literature evidence to rank candidates, and AI systems increasingly help by scoring targets, spotting hidden relationships, and prioritizing experiments. In practice, target identification is an evidence-management problem: the best candidates are not just biologically interesting, but also testable, druggable, and relevant to the disease mechanism.