Posters
Presenting Author Academic/Professional Position
Linwei Li / MS2
Academic Level (Author 1)
Medical Student
Discipline/Specialty (Author 1)
Cancer and Immunology
Academic Level (Author 2)
Medical Student
Discipline/Specialty (Author 2)
Cancer and Immunology
Academic Level (Author 3)
Medical Student
Discipline/Specialty (Author 3)
Cancer and Immunology
Academic Level (Author 4)
Medical Student
Discipline/Specialty (Author 4)
Cancer and Immunology
Academic Level (Author 5)
Medical Student
Discipline/Specialty (Author 5)
Cancer and Immunology
Discipline Track
Clinical Science
Abstract Type
Research/Clinical
Abstract
Background: 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.
Methods: This review was first conceptualized by outlining the key topics to be discussed. It was then organized into subsections corresponding to each topic (established therapies, targeted therapies, and AI). To maintain a focused scope, the selection of publications prioritized studies addressing the pharmacological implications, treatment response, and adverse effects of targeted therapies. Commonly used treatments were identified, and a targeted, retrospective literature search was conducted to gather relevant information. Notably, this review does not follow a formal systematic review protocol. This review also discusses the emerging targeted therapies currently in the pre-clinical or clinical trial phases for HCC, CRC, and pancreatic cancer. These cancers were selected due to their high resistance to treatment, poor response rates, and significant global prevalence. Tables were included to present summarized data from the reviewed publications more clearly.
Results: 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.
Conclusions: We chose to discuss the possibility of including AI in our review, as we have seen the immense potential for AI as a tool to be more patient-specific with improved clinical outcomes. We also believe that AI will eventually be incorporated into medical practices. However, we would like to acknowledge significant challenges, such as logistical challenges to digital pathology, data quality concerns, risk of bias, ethical implications, and potential compromise to patient trust. The current advancement of AI in medicine accompanies a worrying lack of legislative framework, making it susceptible to breaches of patient rights. Therefore, rash adoption of powerful technology is like building a new story on a foundation of quicksand, which will lead to an ultimate collapse. We are optimistic that with careful planning and thoughtful implementation, AI can be incorporated in a way that truly benefits patients while minimizing unintentional harm.
Presentation Type
Poster
Recommended Citation
Li, Linwei; Doppalapudi, Anika; Escamilla, Jennifer; Karithara, Annu; Pham, Christine; Phillip, Angel; Binoy, Anjali; Gullapalli, Sriya; Baldado, Lois; Bellamkonda, Arjun; Gonzalez, Daniela; Ibrahim, Amin; Ramos, Daniela; Sta. Maria, David; Ybanez, Kaitlyn; Zamarron, Hugo; and Mito, Shizue, "Precision medicine and beyond: Evolving roles of targeted therapy, immunotherapy, and artificial intelligence in oncology" (2025). Research Colloquium. 58.
https://scholarworks.utrgv.edu/colloquium/2025/posters/58
Included in
Precision medicine and beyond: Evolving roles of targeted therapy, immunotherapy, and artificial intelligence in oncology
Background: 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.
Methods: This review was first conceptualized by outlining the key topics to be discussed. It was then organized into subsections corresponding to each topic (established therapies, targeted therapies, and AI). To maintain a focused scope, the selection of publications prioritized studies addressing the pharmacological implications, treatment response, and adverse effects of targeted therapies. Commonly used treatments were identified, and a targeted, retrospective literature search was conducted to gather relevant information. Notably, this review does not follow a formal systematic review protocol. This review also discusses the emerging targeted therapies currently in the pre-clinical or clinical trial phases for HCC, CRC, and pancreatic cancer. These cancers were selected due to their high resistance to treatment, poor response rates, and significant global prevalence. Tables were included to present summarized data from the reviewed publications more clearly.
Results: 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.
Conclusions: We chose to discuss the possibility of including AI in our review, as we have seen the immense potential for AI as a tool to be more patient-specific with improved clinical outcomes. We also believe that AI will eventually be incorporated into medical practices. However, we would like to acknowledge significant challenges, such as logistical challenges to digital pathology, data quality concerns, risk of bias, ethical implications, and potential compromise to patient trust. The current advancement of AI in medicine accompanies a worrying lack of legislative framework, making it susceptible to breaches of patient rights. Therefore, rash adoption of powerful technology is like building a new story on a foundation of quicksand, which will lead to an ultimate collapse. We are optimistic that with careful planning and thoughtful implementation, AI can be incorporated in a way that truly benefits patients while minimizing unintentional harm.
