Multifaceted Modulation of Tumor Microenvironment Dynamics: Emerging Cross-Disciplinary Paradigms in Precision Drug...

Cancer is one of the leading global public health challenges, thus creating a pressing need to develop novel therapies that combine concepts from various scientific disciplines. In this review, we have evaluated how advancements in artificial intelligence, cancer research, and materials science have collectively influenced modern cancer therapies. Cancer research, in particular, is focusing on the tumor microenvironment (TME), which is a highly complex, dynamic, and heterogeneous environment consisting of cancer cells, stromal components, immune cells, and paracrine factors that collectively orchestrate cancer development, progression, metastasis, and drug resistance. Modern analytical tools, including artificial intelligence, have been developed to integrate various omics data, medical images, and clinical information to understand TME, detect potential drug targets, and accurately predict drug response in cancer therapy. Simultaneously, advancements in materials science have led to the development of targeted drug delivery systems, including smart drug delivery systems that can be programmed to release drugs in response to tumor-specific stimuli, including enzymatic activity, acidic pH, temperature, or external stimuli, including light, ultrasound, or magnetic fields. The integration of AI modeling with these precision delivery methods is further advancing the strategies aimed at improving the accumulation of anticancer therapeutics at the tumor site while minimizing the systemic toxicity of the treatment. The review also highlights the recent advances of various ligand-mediated targeting strategies that include antibodies, peptides, aptamers, proteins, and small molecule ligands, as well as the application of AI modeling for improving the nanoparticle-based treatment regimens. Overall, these advances are further propelling the development of highly personalized treatment strategies that are effective against cancer. The further integration of these computer modeling tools with the cutting-edge biomaterials technology is expected to show great promise for improving the treatment of cancer while bypassing the TME-mediated barriers.