A Review on Analytical Insights into Impurity Profiling of Selected Anticancer Agents: Tinibs and Taxanes.

Impurity profiling is a critical quality and safety requirement for structurally complex anticancer agents. This review critically analyses impurity-profiling literature (1997-2025) for three tinibs, imatinib mesylate (IMM), dasatinib (DST), and nilotinib, and three taxanes, paclitaxel (PTX), docetaxel (DTX), and cabazitaxel (CTX), encompassing 54 analytical studies. Across the compiled dataset, reversed-phase HPLC accounted for 63.6% of methods, UPLC/ ultra-high-performance LC (UHPLC) for 16.4%, LC-MS/High-Resolution Mass Spectrometry (HRMS) for 9.1%, and GC-MS for 5.5%; high-performance thin-layer chromatography (HPTLC)-MS, headspace GC, and SFC appeared in isolated reports. HPLC/UPLC methods demonstrated LODs of 0.005-2 µg mL-1, whereas LC-MS/MS achieved LODs as low as 0.003-0.005 ng mL-1 for genotoxic impurities in tinibs. GC-based methods were especially valuable for volatile impurities and residual sulfonates, with detection in the low-ppb to sub-µg mL-1 range. Tinib impurity profiles are dominated by process-related, oxidative, nitrosamine, and genotoxic species, while taxane profiles are characterized by epimerization products, deacetylated derivatives, side-chain cleavage products, and precursor-related impurities. Regulatory implications under ICH Q3A(R2), Q3B(R2), M7(R2), S9, and Q3C are discussed, including dose-normalised threshold of toxicological concern (TTC) calculations. An impurity-type versus analytical-technique matrix is proposed to guide method selection. Critical analytical gaps are identified, and future directions encompassing green analytical chemistry (GAC), process analytical technology (PAT), and AI-assisted impurity prediction are outlined.