Submission Tilte
Innovative Drug Research Propelling a New Era of Precision Oncology
Submission Abstract:
Drug-oncology research is leading a new era of precision medicine, becoming a frontier hotspot in cancer treatment. Advancements in molecular biology, genomics, and medicinal chemistry have driven revolutionary changes in cancer cognition and treatment strategies. Gene-targeted drugs provide more precise treatments, improving survival rates for certain cancers. Network pharmacology offers systematic explanations for compound drug mechanisms, promoting the integration of traditional and modern medicine. Big data and bioinformatics applications, such as TCGA and GEO databases, aid in discovering new targets and developing drugs. Mendelian randomization methods provide causal inference tools, enhancing the accuracy of drug effect predictions. These innovative methods improve treatment precision and offer new approaches to solving drug resistance and toxicity issues. However, computational results require rigorous experimental validation to confirm their biological significance and clinical relevance. In vitro experiments, animal models, and clinical trials are necessary steps to translate predictions into therapeutic strategies. The combination of computational predictions and experimental validation accelerates the discovery of new targets and drugs, improving research reliability. The application of artificial intelligence technology promises to accelerate new drug development and reduce costs. This comprehensive research strategy brings hope to patients, driving cancer treatment towards more precise and effective directions.
Despite significant progress in drug-oncology research, numerous challenges remain that require ongoing exploration. These challenges include precise identification and validation of new therapeutic targets, especially discovering targets with broad-spectrum anti-tumor activity; overcoming tumor drug resistance, predicting and resolving resistance mechanisms; optimizing drug combinations to improve efficacy and reduce side effects; accelerating the translation of basic research findings into clinical applications; ensuring data quality, standardization, and result reliability in big data analysis and artificial intelligence technology applications; developing personalized treatment plans, optimizing immunotherapy, predicting and managing treatment-related toxicities; effectively designing and executing validation experiments, including selecting appropriate models, optimizing conditions, interpreting results, establishing standardized processes, and integrating experimental data from different levels; balancing the development costs of innovative drugs with their accessibility. These challenges cover various aspects from the molecular level to clinical applications, requiring interdisciplinary collaboration and innovative thinking to further advance precision cancer therapy.
This special issue aims to compile the latest advances and innovative ideas in the field of drug-oncology research. We particularly welcome studies on gene-targeted drug development, applications of network pharmacology in elucidating mechanisms of compound drugs, utilization of Mendelian randomization in drug-target relationship research, and the use of big data and bioinformatics methods to discover novel cancer treatment targets. We encourage original research articles, review articles, and reports on new technologies and methodologies that can drive progress in this field.