Beyond Current Therapies: In Silico Drug Repurposing as a Strategy to Overcome Tyrosine Kinase Inhibitor Resistance in NSCLC

Tyrosine kinase inhibitor (TKI) resistance in non-small cell lung cancer (NSCLC) poses a major challenge to the long-term success of current targeted treatments. This paper explores this clinical obstacle and advocates for In Silico drug repurposing as an essential, rapid strategy to discover new therapies for various resistance mechanisms, including mutations in EGFR, ALK, ROS1, and MET. By applying advanced computational techniques, combining extensive genomic and phenotypic data, and utilizing sophisticated machine learning, this method provides a transformative way to find new uses for existing drugs. This approach significantly reduces the long development times, high costs, and failure rates associated with traditional new drug discovery. Although preclinical results are promising and clinical efforts are underway, there are no approved repurposed drugs specifically targeting TKI resistance in NSCLC, which remains a significant therapeutic challenge. We highlight the need for focused research to turn In Silico findings into practical clinical solutions, broadening treatment options and improving patient care in NSCLC.