From Bench to Algorithm: A Five-year Review on Targeting HER2, EGFR, and VEGFR in Breast Cancer

Introduction:: Breast cancer remains a leading cause of cancer-related mortality among women worldwide. Resistance to monotherapies targeting individual receptors such as HER2, EGFR, or VEGFR has underscored the need for multi-targeted approaches. Recent advances in computational modeling, synthetic chemistry, and clinical research have facilitated the discovery of novel therapeutic candidates capable of overcoming resistance and enhancing treatment efficacy. Methods:: A comprehensive literature review was conducted using PubMed, Scopus, ScienceDirect, and Web of Science. In PubMed, filters were applied to restrict the search to studies published between 2019 and 2024. Keywords included “breast cancer,” “HER2,” “EGFR,” “VEGFR,” “multi-target therapy,” “computational drug design,” and “synthetic derivatives.” Studies were screened for relevance, with emphasis on molecular docking, molecular dynamics, virtual screening, synthetic heterocycles, and clinical trial outcomes. Data were synthesized to evaluate therapeutic progress across computational, synthetic, and clinical domains. Results:: Computational strategies identified promising lead compounds through docking, dynamics, and virtual screening, with increasing adoption of AI-driven drug discovery. Synthetic studies advanced from traditional scaffolds such as quinazolines and imidazoles to novel heterocycles and hybrid inhibitors. Clinically, the therapeutic landscape expanded from trastuzumab and cetuximab to anti-VEGF agents and antibody-drug conjugates, culminating in personalized therapies. Collectively, these approaches highlight the convergence of in silico, in vitro, and clinical innovations for breast cancer treatment. Discussion:: Integration of computational predictions with synthetic chemistry and clinical validation has accelerated the development of multi-targeted therapies. However, challenges remain in translating in silico predictions into clinically viable drugs, addressing drug resistance, and ensuring safety. The timeline of advances illustrates a progressive shift towards precision oncology, yet further optimization of multi-target strategies is required for durable outcomes. Conclusion:: Multi-targeted strategies against HER2, EGFR, and VEGFR represent a promising direction in breast cancer therapy. Advances in computational tools, novel synthetic derivatives, and clinical interventions collectively provide a foundation for next-generation therapeutics. Future research should emphasize translational studies and personalized treatment approaches to overcome resistance and improve patient survival.