Precision Oncology: Current Status of Targeted Therapies and Prospective Advances
With an emphasis on precision intervention that blocks particular biochemical pathways necessary for tumor growth and survival, targeted therapies in cancer provide a revolutionary approach to treatment. This review examines the range of targeted medicines, including biologics, small molecule inhibitors, and cell and gene therapies, emphasizing their benefits, drawbacks, and new developments. Cancer-driving kinases and other signaling proteins can be directly inhibited by small molecule inhibitors, which frequently work intracellularly. Monoclonal antibodies and other biologics use extracellular targets to interfere with signaling and identify cancer cells for immune destruction. By altering biological pathways or specifically targeting cancer genomes, cell and gene therapies—such as CAR-T cells and CRISPR-based interventions—offer individualized approaches. Notwithstanding their accuracy, each modality has drawbacks such as biologics may be constrained by immune-related side effects, cell and gene therapies are difficult to produce and deliver, and small molecule inhibitors may cause drug resistance through mutations. Combination treatments, innovative delivery systems, and adaptive dosing techniques are some of the current solutions that try to reduce these problems. From drug development and patient stratification to real-time treatment efficacy monitoring, artificial intelligence presents a viable path toward optimizing targeted medicines. AI can detect resistance patterns, find predictive biomarkers, and recommend combinatory strategies by evaluating large datasets, opening the door to customized, adaptable cancer treatments.
Authors
- Swati Dhar (ORCID: https://orcid.org/0000-0002-3415-4767)
Institutions
- PAREXEL International (United Kingdom) (GB)
- PAREXEL International (United States) (US)
Publication Details
- Journal
- Premier journal of science.
- Published
- 2024-12-27
- DOI
- https://doi.org/10.70389/pjs.100039
- Primary Topic
- Cancer Genomics and Diagnostics
- Type
- article
- Field-Weighted Citation Impact
- 0.00