Synergizing metabolomics and artificial intelligence for advancing precision oncology

Area of Science:

• Oncology
• Metabolomics
• Artificial Intelligence

Background:

• Metabolomics is a key tool in precision oncology for biomarker discovery and treatment monitoring.
• Integrating artificial intelligence (AI) with metabolomics enhances data analysis and interpretation of metabolic networks.

Purpose of the Study:

• To explore recent advances in AI-driven metabolomics for precision oncology.
• To highlight the advantages of AI in metabolomics for improving patient outcomes.

Main Methods:

• Review of recent advances in AI-driven metabolomics applications.
• Discussion of AI's role in optimizing metabolomic data acquisition and analysis.
• Exploration of multiomics integration facilitated by AI.

Main Results:

• AI amplifies the potential of current metabolomics platforms.
• AI accelerates research progress in precision oncology.
• AI-driven metabolomics shows promise for improved patient outcomes.

Conclusions:

• AI-driven metabolomics offers significant advantages for precision oncology.
• Translating AI-driven metabolomics into clinical practice presents opportunities and challenges.
• Further research is needed to fully realize the clinical potential of AI in metabolomics for cancer care.