Current clinical practices, which focus on a small number of biochemicals directly relevant to the pathophysiology within patients, only describe a very limited metabolome of the patient, and do not generally consider the interactions of these small molecules. This lack of information may prevent clinicians from making the best possible therapeutic interventions in time to improve patient care. Various post-genomics (’omics) approaches have been used for therapeutic interventions previously. Metabolomics now a well-established ’omics approach, has been widely adopted as a novel approach for biomarker discovery and in tandem with genomics (especially SNPs and GWAS) has the potential for providing systemic understanding of the underlying causes of pathology. In this review, we discuss the relevance of metabolomics approaches in clinical sciences and its potential for biomarker discovery which may help guide clinical interventions. Although a powerful and potentially high throughput approach for biomarker discovery at the molecular level, true translation of metabolomics into clinics is an extremely slow process. Quicker adaptation of biomarkers discovered using metabolomics can be possible with novel portable and wearable technologies aided by clever data mining as well as deep learning and artificial intelligence; we shall also discuss this with an eye to the future of precision medicine where metabolomics can be delivered to the masses
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