Strategies for the drug development of cancer therapeutics

作者：Hongyan Liu, Yanpin Ma, Wenjuan Chen, Xinyu Gu, Jiachun Sun, Penghui Li · 发表于：Frontiers in Pharmacology · 年份：2025 · DOI：10.3389/fphar.2025.1656012 · 被引用次数：2 · 研究领域：Computational Drug Discovery Methods、Bioinformatics and Genomic Networks、Gene Regulatory Network Analysis

Cancer is a global health threat, with its treatment modalities transitioning from single therapies to integrated treatments. This paper systematically explores the key technological systems in modern cancer treatment and their application value. Modern cancer treatment relies on four core technological pillars: omics, bioinformatics, network pharmacology (NP), and molecular dynamics (MD) simulation. Omics technologies integrate various biological molecular information, such as genomics, proteomics and metabolomics, providing foundational data support for drug research. But the differences in data and the challenges of integrating it often lead to biased predictions, and that's a big limitation for this technology. Bioinformatics utilizes computer science and statistical methods to process and analyze biological data, aiding in the identification of drug targets and the elucidation of mechanisms of action. It is important to note that the prediction accuracy largely depends on the algorithm chosen. Consequently, this dependence may affect the reliability of the research results. NP, based on systems biology, studies drug-target-disease networks, revealing the potential for multitargeted therapies. That said, this method may overlook important aspects of biological complexity, such as variations in protein expression. This oversight can lead to overestimating the effectiveness of multi-targeted therapies, resulting in false positives in efficacy assessments, which somewhat lim...