Standardised management of
tuberculosis may soon be replaced by individualised,
precision medicine-guided
therapies informed with knowledge provided by the field of systems biology. Systems biology is a rapidly expanding field of computational and mathematical analysis and modelling of complex
biological systems that can provide insights into mechanisms underlying
tuberculosis, identify novel
biomarkers, and help to optimise prevention, diagnosis and treatment of disease. These advances are critically important in the context of the evolving epidemic of
drug-resistant tuberculosis. Here, we review the available evidence on the role of systems biology approaches - human and mycobacterial genomics and transcriptomics, proteomics, lipidomics/metabolomics, immunophenotyping, systems pharmacology and gut microbiomes - in the management of
tuberculosis including prediction of risk for
disease progression, severity of mycobacterial virulence and drug resistance, adverse events, comorbidities, response to
therapy and treatment outcomes. Application of the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach demonstrated that at present most of the studies provide "very low" certainty of evidence for answering clinically relevant questions. Further studies in large prospective cohorts of patients, including randomised clinical trials, are necessary to assess the applicability of the findings in
tuberculosis prevention and more efficient clinical management of patients.