AI-POWERED METABOLIC INTELLIGENCE: REDEFINING PERSONALIZED CANCER THERAPY THROUGH MULTI-OMICS DATA

*Bablu Malhotra, Dr. Owais Zargar, Dr. Nashrah Ashraf and Dr. Ayat Albina

Cancer is a worldwide health concern characterised by the unchecked growth, division, and metabolism of tissues and individual cells, which feeds the tumour and permits its proliferation as it becomes resistant to treatment. Since cancer cells can withstand stress and many tumours are diverse, surgery, chemotherapy, and radiation have not shown to be viable long-term remedies. Through the use of glucose, tumour metabolism regulates several cellular metabolisms and is linked to the advancement of cancer. Due to the tumour's incredibly high energy requirements and rapid development, pathways involved in glycolysis, amino acid metabolism, and lipid metabolism are reorganised. These metabolic changes may lead to novel strategies for cancer patients' focused treatments. Therefore, this knowledge of these metabolic alterations will help create more effective and individualised treatment plans. Artificial intelligence has emerged as a greatly improved tool in the field of cancer to help researchers analyse large datasets of genetic and metabolic data to find patterns that would not otherwise be seen. These prediction tools are helpful when dealing with medication resistance, mapping the metabolism of tumours, and finding biomarkers that show how a tumour reacts to particular therapies. The machine learning models use proteomics, genomes, and metabolomics data to improve understanding of tumour behaviour. This makes it possible to develop therapeutic strategies that will stop particular metabolic pathways that are only utilised by malignant cells. AI is also enhancing real-time tumour monitoring, which enables physicians to modify treatment plans according to the distinct metabolic profiles of each patient.