Omics : a journal of integrative biology
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Pharmaceutical industry and the art and science of drug development are sorely in need of novel transformative technologies in the current age of digital health and artificial intelligence (AI). Often described as game-changing technologies, AI and machine learning algorithms have slowly but surely begun to revolutionize pharmaceutical industry and drug development over the past 5 years. In this expert review, we describe the most frequently used machine learning algorithms in drug development pipelines and the -omics databases well poised to support machine learning and drug discovery. ⋯ As with system sciences, AI and machine learning embody a system scale and Big Data driven vision for drug discovery and development. We conclude with a future outlook on the ways in which machine learning approaches can be implemented to buttress and expedite drug discovery and precision medicine. As AI and machine learning are rapidly entering pharmaceutical industry and the art and science of drug development, we need to critically examine the attendant prospects and challenges to benefit patients and public health.
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Medical decision-making is revolutionizing with the introduction of artificial intelligence and machine learning. Yet, traditional algorithms using biomarkers to optimize drug treatment continue to be important and necessary. In this context, early diagnosis and rational antimicrobial therapy of sepsis and lower respiratory tract infections (LRTI) are vital to prevent morbidity and mortality. ⋯ S. real-world data. We suggest that future CEA studies in other U. S. and worldwide settings are warranted in the current age when PCT and other decision algorithms are increasingly deployed in precision therapeutics and evidence-based medicine.
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This article offers an analysis of the ways in which digital health innovations are being coproduced by mainstreaming of artificial intelligence (AI), the Internet of Things (IoT), and cyber-physical systems (CPS) in health care. CPS blurs the boundaries between the physical and virtual worlds, and creates a dynamic digital map of all things in existence that can be analyzed in ways that are much more sophisticated than a bar code scanning system. Examples of CPS include self-driving cars, wearables for digital monitoring of heart arrhythmias, industrial AI-powered robots in smart factories and health robots delivering home care services to disabled persons and rural communities. ⋯ A societal issue such as privacy may emerge in different forms and intensities in the physical and virtual contexts. Digital data are highly fluid and can rapidly move across spaces and places, whereas the physical data and humans are much slower and exist in different scales than our digital footprints. It is therefore timely for the system sciences and integrative biology communities to critically engage with digital health and the related technologies, such as AI, IoT, and CPS.
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Most solid tumors become therapy resistant and will relapse, with no durable treatment option available. One major impediment to our understanding of cancer biology and finding innovative approaches to cancer treatment stems from the lack of better preclinical tumor models that address and explain tumor heterogeneity and person-to-person differences in therapeutic and toxic responses. Past cancer research has been driven by inadequate in vitro assays utilizing two-dimensional monolayers of cancer cells and animal models. ⋯ Generation of near-perfect physiological microenvironments allow 3D organoids to couple with gene editing tools, such as the clustered regularly interspersed short palindromic repeat (CRISPR)/CRISPR-associated 9 and the transcription activator-like effector nucleases to model human diseases, offering distinct advantages over current models. We explain in this expert review that through recapitulating patients' normal and tumor tissues, organoid technology can markedly advance personalized medicine and help reveal once hidden aspects of cancers. The use of defined tissue- or organ-specific matrices, among other factors, will likely allow organoid technology to realize its potential in innovating many fields of life sciences.
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Review
The Gut Microbiome and Mental Health: Implications for Anxiety- and Trauma-Related Disorders.
Biological psychiatry research has long focused on the brain in elucidating the neurobiological mechanisms of anxiety- and trauma-related disorders. This review challenges this assumption and suggests that the gut microbiome and its interactome also deserve attention to understand brain disorders and develop innovative treatments and diagnostics in the 21st century. The recent, in-depth characterization of the human microbiome spurred a paradigm shift in human health and disease. ⋯ Other factors that shape the gut microbiome should be considered to obtain a holistic view of the factors at play in the complex interactome linked to the MGB. In all, we underscore the importance of microbiome science, and gut microbiota in particular, as emerging critical players in mental illness and maintenance of mental health. This new frontier of biological psychiatry and postgenomic medicine should be embraced by the mental health community as it plays an ever-increasing transformative role in integrative and holistic health research in the next decade.