What is lead optimization in drug discovery and what parameters are optimized?

Lead optimization transforms initial hit compounds into drug candidates with improved properties. Parameters optimized: 1) Potency - improve target affinity through SAR (structure-activity relationship) studies; typically seek nM to pM range for biologics. 2) Selectivity - reduce off-target activity; assess against related targets and broader panels. 3) ADME properties - absorption, distribution, metabolism, excretion; for biologics: PK, tissue penetration, stability. 4) Safety - minimize toxicity, genotoxicity, hERG liability. 5) Drug-like properties - appropriate MW, solubility, stability. 6) Manufacturability - synthetic feasibility, scalability, cost. Approaches include: medicinal chemistry modifications, computational modeling (docking, QSAR), fragment growing/linking, parallel synthesis for SAR exploration, and developability assessment. For antibodies: affinity maturation, humanization, Fc engineering, format optimization. Iterative cycles of design-make-test-analyze. Stage-gates evaluate candidates against target product profile.