Targeting metabolic pathways provides novel therapeutic prospects as metabolic reprogramming is becoming more widely recognized as a characteristic of a variety of disorders. Despite preclinical research and clinical trials demonstrating the potential of metabolic treatments, the complicated nature and flexibility of cellular metabolic networks prevent their advancement into effective treatments. Compared to conventional methods, metabolism-based treatment may be able to interfere with important functions in diseased cells and their surroundings, allowing for more individualized and accurate treatments. However, there are still challenges associated with overcoming variability and resistance, which highlights the necessity of advanced single-cell analysis methods. Personalizing metabolic therapies and optimizing treatment plans for individual patients are becoming feasible with the integration of artificial intelligence (AI) and machine learning (ML). Furthermore, patient stratification depends significantly on the application of metabolomics and advanced imaging methods, which allow for a more accurate decision of treatment modalities. This chapter provides a comprehensive overview of recent clinical trials and translational advancements in metabolic targeting, with a focus on small-molecule inhibitors and multi-omics technologies. New developments in metabolic research, from mechanistic understanding to clinical applications, are transforming the biomedical treatment while offering novel opportunities for disease management rather than traditional approaches.