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

Created on 24 Aug 2026

Authors

Aggarapu Susmitha, Galla Rajitha, Gireesh Kumar Eri, Kavya Orupalli, Charishma Naga Sai Batta, Bommireddy Mounika

Published in

Critical reviews in analytical chemistry. Pages 1-30. Aug 23, 2026. Epub Aug 23, 2026.

Abstract

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.

PMID:
42634006
Bibliographic data and abstract were imported from PubMed on 24 Aug 2026.

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