Human Microbiome and Learning Healthcare Systems: Integrating Research and Precision Medicine for Inflammatory Bowel Disease

人类微生物组与学习型医疗保健系统:整合研究与精准医疗以治疗炎症性肠病

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Abstract

Healthcare institutions face widespread challenges of delivering high-quality and cost-effective care, while keeping up with rapid advances in biomedical knowledge and technologies. Moreover, there is increased emphasis on developing personalized or precision medicine targeted to individuals or groups of patients who share a certain biomarker signature. Learning healthcare systems (LHS) have been proposed for integration of research and clinical practice to fill major knowledge gaps, improve care, reduce healthcare costs, and provide precision care. To date, much discussion in this context has focused on the potential of human genomic data, and not yet on human microbiome data. Rapid advances in human microbiome research suggest that profiling of, and interventions on, the human microbiome can provide substantial opportunity for improved diagnosis, therapeutics, risk management, and risk stratification. In this study, we discuss a potential role for microbiome science in LHSs. We first review the key elements of LHSs, and discuss possibilities of Big Data and patient engagement. We then consider potentials and challenges of integrating human microbiome research into clinical practice as part of an LHS. With rapid growth in human microbiome research, patient-specific microbial data will begin to contribute in important ways to precision medicine. Hence, we discuss how patient-specific microbial data can help guide therapeutic decisions and identify novel effective approaches for precision care of inflammatory bowel disease. To the best of our knowledge, this expert analysis makes an original contribution with new insights poised at the emerging intersection of LHSs, microbiome science, and postgenomics medicine.

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