Personalized Drug Therapy in Oncology: Clinical Insights and Future Perspectives

Cancer treatment has made progress through personalized medical therapies that tailor strategies based on patient characteristics. This article explores the application of personalized therapies in oncology, including biomarker-guided therapies, liquid biopsies, next-generation sequencing, personalized immunotherapy, and nanotechnology-based drug delivery. Focusing on personalized drug therapy in oncology, this article delves into its clinical application. It elaborates on the use of biomarkers to guide medication, liquid biopsy for auxiliary diagnosis, and personalized immunotherapy, showcasing their role in advancing precision medicine. At the same time, it discusses the challenges faced in this field, such as high costs and complex data processing, and looks forward to the future prospects of personalized drug therapy in oncology. Despite advancements, challenges such as high costs and complex data analysis issues still persist.

Authors

Institutions

Publication Details

Journal
Journal of Clinical Medicine Research
Published
2025-04-22
DOI
https://doi.org/10.32629/jcmr.v6i1.3713
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Personalized Drug Therapy in Oncology: Clinical Insights and Future Perspectives

Chen Liang
2 links
Journal of Clinical Medicine Research
Computational Drug Discovery Methods
article

Personalized Drug Therapy in Oncology: Clinical Insights and Future Perspectives

Chen Liang
article en

Abstract

Cancer treatment has made progress through personalized medical therapies that tailor strategies based on patient characteristics. This article explores the application of personalized therapies in oncology, including biomarker-guided therapies, liquid biopsies, next-generation sequencing, personalized immunotherapy, and nanotechnology-based drug delivery. Focusing on personalized drug therapy in oncology, this article delves into its clinical application. It elaborates on the use of biomarkers to guide medication, liquid biopsy for auxiliary diagnosis, and personalized immunotherapy, showcasing their role in advancing precision medicine. At the same time, it discusses the challenges faced in this field, such as high costs and complex data processing, and looks forward to the future prospects of personalized drug therapy in oncology. Despite advancements, challenges such as high costs and complex data analysis issues still persist.

Journal of Clinical Medicine ResearchVol. 6(1)
Guangdong Polytechnic of Science and Technology (CN), Zhuhai Institute of Advanced Technology (CN)
Openalex Percentile: Top 90%
Computational Drug Discovery Methods
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.