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Updated: Mar 19, 2026

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System
Published on: December 11, 2016
Individualized network-based drug repositioning infrastructure for precision oncology in the panomics era
Abstract:
Advances in next-generation sequencing technologies have generated the data supporting a large volume of somatic alterations in several national and international cancer genome projects, such as The Cancer Genome Atlas and the International Cancer Genome Consortium. These cancer genomics data have facilitated the revolution of a novel oncology drug discovery paradigm from candidate target or gene studies toward targeting clinically relevant driver mutations or molecular features for precision cancer therapy. This focuses on identifying the most appropriately targeted therapy to an individual patient harboring a particularly genetic profile or molecular feature. However, traditional experimental approaches that are used to develop new chemical entities for targeting the clinically relevant driver mutations are costly and high-risk. Drug repositioning, also known as drug repurposing, re-tasking or re-profiling, has been demonstrated as a promising strategy for drug discovery and development. Recently, computational techniques and methods have been proposed for oncology drug repositioning and identifying pharmacogenomics biomarkers, but overall progress remains to be seen. In this review, we focus on introducing new developments and advances of the individualized network-based drug repositioning approaches by targeting the clinically relevant driver events or molecular features derived from cancer panomics data for the development of precision oncology drug therapies (e.g. one-person trials) to fully realize the promise of precision medicine. We discuss several potential challenges (e.g. tumor heterogeneity and cancer subclones) for precision oncology. Finally, we highlight several new directions for the precision oncology drug discovery via biotherapies (e.g. gene therapy and immunotherapy) that target the 'undruggable' cancer genome in the functional genomics era.
Insights
Precision oncology leverages cancer genomics data for targeted therapies. This review explores individualized network-based drug repositioning to overcome challenges and advance precision cancer medicine.
Area of Science:
- Oncology
- Genomics
- Pharmacology
Background:
- Next-generation sequencing has generated vast cancer genomics data, shifting drug discovery towards precision cancer therapy targeting driver mutations.
- Traditional methods for developing targeted cancer drugs are costly and high-risk, necessitating alternative strategies like drug repositioning.
- Computational approaches for oncology drug repositioning and biomarker identification show promise but require further development.
Purpose of the Study:
- To review advances in individualized network-based drug repositioning for precision oncology.
- To highlight the use of cancer panomics data for developing targeted therapies and personalized medicine.
- To discuss challenges and future directions in precision oncology drug discovery.
Main Methods:
- Review of current literature on network-based drug repositioning in oncology.
- Analysis of cancer panomics data for identifying clinically relevant driver events and molecular features.
- Exploration of computational techniques for drug repositioning and pharmacogenomics biomarker discovery.
Main Results:
- Individualized network-based approaches offer a promising strategy for precision oncology drug development.
- Targeting specific molecular features derived from cancer panomics data can lead to effective precision therapies.
- Biotherapies like gene therapy and immunotherapy present new avenues for targeting the 'undruggable' cancer genome.
Conclusions:
- Precision medicine in oncology can be advanced through individualized network-based drug repositioning.
- Addressing challenges like tumor heterogeneity is crucial for successful precision oncology.
- Future research should focus on biotherapies and targeting the complex cancer genome for novel drug discovery.
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