ificial intelligence (AI) demonstrates unprecedented potential in the study of tumor drug resistance and precision therapy. With the rapid growth of multi-omics data and biomedical information

AI effectively deciphers the complex mechanisms underlying drug resistance

such as gene mutations

overexpression of drug efflux pumps

and changes in the tumor microenvironment. By leveraging the rapid growth of multi-omics data

AI identifies complex drug resistance mechanisms

including genetic mutations

overexpression of drug efflux pumps

and activation of alternative signaling pathways

as well as changes in the tumor microenvironment

such as hypoxia

immune evasion

and stromal interactions. AI promotes personalized treatment by accurately predicting patient responses and resistance risks

thereby supporting the design and dynamic adjustment of individualized therapeutic strategies. AI also plays a pivotal role in the optimization of drug combinations

the development of resistance-reversal strategies

and the design of nano-drug delivery systems. This review explores the cutting-edge advances made in AI and its key applications in tumor drug resistance research and analyzes its future prospects across interdisciplinary fields. Despite remaining challenges involving data privacy and model interpretability

the integration of AI with emerging technologies

such as single-cell sequencing

and cross-disciplinary collaboration will significantly advance the understanding of drug resistance mechanisms and promote progress in precision oncology.