Abstract

Recent developments in nanotechnology and computational modelling have opened new avenues to address these challenges of treating cancer. One such innovation is NanoQSAR (Quantitative Structure- Activity Relationship) modelling, a powerful tool that combines the predictive capabilities of QSAR with nanotechnology’s precision. This mini review discusses how NanoQSAR intersects cancer treatment and how it holds the potential to revolutionize drug design, optimization, and personalized therapy. Key methodologies of NanoQSAR, its application in the prediction of biological activity in nanomaterials, and how it enhances targeted cancer therapies are discussed. Also, the potential integration of NanoQSAR with machine learning and artificial intelligence to help accelerate the discovery of novel anticancer agents has been investigated. Finally, challenges and directions for future research in the field are presented, suggesting that further research is urgently needed to fully realize the promise of NanoQSAR in cancer therapy.