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A system pharmacology multi-omics approach toward uncontrolled pediatric asthma
Mahmoud I. Abdel-Aziz, Mario Gorenjak, Uroš Potočnik, 2021, original scientific article

Abstract: There is a clinical need to identify children with poor asthma control as early as possible, to optimize treatment and/or to find therapeutic alternatives. Here, we present the “Systems Pharmacology Approach to Uncontrolled Pediatric Asthma” (SysPharmPediA) study, which aims to establish a pediatric cohort of moderate-to-severe uncontrolled and controlled patients with asthma, to investigate pathophysiological mechanisms underlying uncontrolled moderate-to-severe asthma in children on maintenance treatment, using a multi-omics systems medicine approach. In this multicenter observational case–control study, moderate-to-severe asthmatic children (age; 6–17 years) were included from four European countries (Netherlands, Germany, Spain, and Slovenia). Subjects were classified based on asthma control and number of exacerbations. Demographics, current and past patient/family history, and clinical characteristics were collected. In addition, systems-wide omics layers, including epi(genomics), transcriptomics, microbiome, proteomics, and metabolomics were evaluated from multiple samples. In all, 145 children were included in this cohort, 91 with uncontrolled (median age = 12 years, 43% females) and 54 with controlled asthma (median age = 11.7 years, 37% females). The two groups did not show statistically significant differences in age, sex, and body mass index z-score distribution. Comprehensive information and diverse noninvasive biosampling procedures for various omics analyses will provide the opportunity to delineate underlying pathophysiological mechanisms of moderate-to-severe uncontrolled pediatric asthma. This eventually might reveal novel biomarkers, which could potentially be used for noninvasive personalized diagnostics and/or treatment.
Keywords: pediatric asthma, uncontrolled asthma, omics, systems medicine
Published in DKUM: 02.08.2023; Views: 210; Downloads: 15
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Translational and personalized medicine
Krešimir Pavelić, Tamara Martinović, Sandra Kraljević-Pavelić, 2015, original scientific article

Abstract: The idea behind personalized medicine is to tailor health care to an individual’s unique genetic makeup. Hitherto, “one size fits all” approach was used in medicine. With the rise of personal medicine, we are moving towards a more precise, predictable and powerful medicine that is customized for each individual patient. To allow for an improvement in the acceleration and efficacy of drug development, high-throughput methods (“omics”) are rapidly being developed. This leads to understanding of multiple factors that are involved in disease progress on an individual level. In order to analyze the great amount of data that is collected from such experiments, one has to turn to systems biology, an interdisciplinary science that studies complex interactions within a biological system. Finally, translational medicine comes into play, by “translating” the information gathered from research into diagnostic tools, medicines and policies, with the final goal of improving individuals’ health. Personalized medicine is one of the future, and it will revolutionize the current practice of diagnosis-based medicine, once fully developed.
Keywords: personalized medicine, translational medicine, clinic, high-throughput methods, systems biology
Published in DKUM: 08.10.2018; Views: 934; Downloads: 344
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Some ideas about intelligent medical system design
Peter Kokol, Tatjana Welzer-Družovec, 1999, original scientific article

Abstract: Mechanical systems increase ouur physical abilities (cranes to lift vast amounts, telescopes to see farther, etc.), but intelligent systems are power tools for heavy lifting in the information world - they complement, extend, and amplify our ability to think and solve problems. In the present paper we will introduce some thoughts and ideas about intelligent medical systems design and the use of MetaMet. A specific design approach constructed with MetaMet will be presented and discussed.
Keywords: intelligent systems, MetaMet, medicine
Published in DKUM: 01.06.2012; Views: 1657; Downloads: 107
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