Precision medicine and beyond: Evolving roles of targeted therapy, immunotherapy, and artificial intelligence in oncology

Authors

Linwei Li, The University of Texas Rio Grande ValleyFollow
Anika Doppalapudi, The University of Texas Rio Grande ValleyFollow
Jennifer Escamilla, The University of Texas Rio Grande ValleyFollow
Annu Karithara, The University of Texas Rio Grande ValleyFollow
Christine Pham, The University of Texas Rio Grande ValleyFollow
Angel Phillip, The University of Texas Rio Grande ValleyFollow
Sriya Gullapalli, The University of Texas Rio Grande ValleyFollow
Lois Baldado, The University of Texas Rio Grande ValleyFollow
Arjun Bellamkonda, The University of Texas Rio Grande ValleyFollow
Daniela Gonzalez, The University of Texas Rio Grande ValleyFollow
Amin Ibrahim, The University of Texas Rio Grande ValleyFollow
David Sta. Maria, The University of Texas Rio Grande ValleyFollow
Kaitlyn Ybanez, The University of Texas Rio Grande ValleyFollow
Hugo Zamarron, The University of Texas Rio Grande ValleyFollow
Shizue Mito, The University of Texas Rio Grande ValleyFollow

Document Type

Article

Publication Date

7-30-2025

Abstract

Precision medicine in oncology is an evolving therapeutic approach that leverages genetic, clinical, and biomarker data to tailor treatments to individual patients. This review explores the three core pillars of modern precision oncology: targeted therapy, immunotherapy, and the integration of artificial intelligence (AI) into clinical practice. Targeted therapies, including monoclonal antibodies and antibody-drug conjugates, selectively inhibit molecular pathways involved in tumor growth. While conventional chemotherapy remains the backbone of treatment and has improved remission rates, its cytotoxic nature limits broader applicability and increases the risk of comorbidities. Immunotherapies, particularly immune checkpoint inhibitors and chimeric antigen receptor T-cell therapies, have transformed treatment for hematologic malignancies and are now being adapted for solid tumors such as colorectal, pancreatic, and hepatocellular carcinomas through novel combination regimens. This review also highlights the therapeutic potential of modulating the tumor microenvironment and introduces emerging modalities such as neoantigen vaccines and microRNA-based therapies. Furthermore, we outline the expanding role of AI in enhancing cancer diagnosis, drug development, and clinical decision-making. By integrating computational tools with molecular therapies, precision medicine rapidly advances toward individualized data-driven care. This review provides an overview of established therapies in the current clinical practice, novel regimens, and emerging AI technologies. Despite ongoing challenges, such as resistance and toxicity, precision medicine demonstrates significant promise in improving oncologic outcomes and transforming cancer care.

Comments

© 2025 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )

Recommended Citation

Li, L., Doppalapudi, A., Escamilla, J., Karithara, A., Pham, C., Phillip, A., ... & Mito, S. (2025). Precision medicine and beyond: Evolving roles of targeted therapy, immunotherapy, and artificial intelligence in oncology. INNOSC Theranostics and Pharmacological Sciences, 8(3), 35-58. https://doi.org/10.36922/ITPS025140018

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Publication Title

INNOSC Theranostics and Pharmacological Sciences

DOI

10.36922/ITPS025140018

Academic Level

medical student

Mentor/PI Department

Medical Education