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10.1016/j.jep.2020.113477 http://scihub22266oqcxt.onion/10.1016/j.jep.2020.113477 33098971!7577282!33098971     free     free     free Deprecated: Implicit conversion from float 227.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 227.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 227.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 227.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 227.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 261.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 261.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 261.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 261.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 261.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       J+Ethnopharmacol 2021 ; 267 (ä): 113477 Nephropedia Template TP {{tp|p=33098971|t=2021. Medicine in motion: Opportunities, challenges and data analytics-based solutions for traditional medicine integration into western medical practice |pdf=|usr=}}{{33098971}} gab.com Text Medicine in motion: Opportunities, challenges and data analytics-based solutions for traditional medicine integration into western medical practice JO: J Ethnopharmacol http://www.kidney.de/pget.php?&tw=1&pmid=33098971 #FOAvip ETHNOPHARMACOLOGICAL RELEVANCE: Traditional pharmacopeias have been developed by multiple cultures and evaluated for efficacy and safety through both historical/empirical iteration and more recently through controlled studies using Western scientific paradigms and an increasing emphasis on data science methodologies for network pharmacology. Traditional medicines represent likely sources of relatively inexpensive drugs for symptomatic management as well as potential libraries of new therapeutic approaches. Leveraging this potential requires hard evidence for efficacy that separates science from pseudoscience. MATERIALS AND METHODS: We performed a review of non-Western medical systems and developed case studies that illustrate the epistemological and practical translative barriers that hamper their transition to integration with Western approaches. We developed a new data analytics approach, in silico convergence analysis, to deconvolve modes of action, and potentially predict desirable components of TM-derived formulations based on computational consensus analysis across cultures and medical systems. RESULTS: Abstraction, simplification and altered dose and delivery modalities were identified as factors that influence actual and perceived efficacy once a medicine is moved from a non-Western to Western setting. Case studies on these factors highlighted issues with translation between non-Western and Western epistemologies, including those where epistemological and medicinal systems drive markets that can be epicenters for zoonoses such as the novel Coronavirus. The proposed novel data science approach demonstrated the ability to identify and predict desirable medicinal components for a test indication, pain. CONCLUSIONS: Relegation of traditional therapies to the relatively unregulated nutraceutical industry may lead healthcare providers and patients to underestimate the therapeutic potential of these medicines. We suggest three areas of emphasis for this field: First, vertical integration and embedding of traditional medicines into healthcare systems would subject them to appropriate regulation and evidence-based practice, as viable integrative implementation mode. Second, we offer a new Bradford-Hill-like framework for setting research priorities and evaluating efficacy, with the goal of rescuing potentially valuable therapies from the nutraceutical market and discrediting those that are pseudoscience. Third, data analytics pipelines offer new capacity to generate new types of TMS-inspired medicines that are rationally-designed based on integrated knowledge across cultures, and also provide an evaluative framework against which to test claims of fidelity and efficacy to TMS made for nutraceuticals. Twit Text FOAVip Medicine in motion: Opportunities, challenges and data analytics-based solutions for traditional medicine integration into western medical practice ????J Ethnopharmacol http://www.kidney.de/pget.php?&tw=1&pmid=33098971 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33098971 #FOAvip English Wikipedia <ref>{{Cite pmid|33098971}}</ref> Medicine in motion: Opportunities, challenges and data analytics-based solutions for traditional medicine integration into western medical practice #MMPMID33098971 Jansen C; Baker JD; Kodaira E; Ang L; Bacani AJ; Aldan JT; Shimoda LMN; Salameh M; Small-Howard AL; Stokes AJ; Turner H; Adra CN J Ethnopharmacol 2021[Mar]; 267 (ä): 113477 PMID33098971show ga ETHNOPHARMACOLOGICAL RELEVANCE: Traditional pharmacopeias have been developed by multiple cultures and evaluated for efficacy and safety through both historical/empirical iteration and more recently through controlled studies using Western scientific paradigms and an increasing emphasis on data science methodologies for network pharmacology. Traditional medicines represent likely sources of relatively inexpensive drugs for symptomatic management as well as potential libraries of new therapeutic approaches. Leveraging this potential requires hard evidence for efficacy that separates science from pseudoscience. MATERIALS AND METHODS: We performed a review of non-Western medical systems and developed case studies that illustrate the epistemological and practical translative barriers that hamper their transition to integration with Western approaches. We developed a new data analytics approach, in silico convergence analysis, to deconvolve modes of action, and potentially predict desirable components of TM-derived formulations based on computational consensus analysis across cultures and medical systems. RESULTS: Abstraction, simplification and altered dose and delivery modalities were identified as factors that influence actual and perceived efficacy once a medicine is moved from a non-Western to Western setting. Case studies on these factors highlighted issues with translation between non-Western and Western epistemologies, including those where epistemological and medicinal systems drive markets that can be epicenters for zoonoses such as the novel Coronavirus. The proposed novel data science approach demonstrated the ability to identify and predict desirable medicinal components for a test indication, pain. CONCLUSIONS: Relegation of traditional therapies to the relatively unregulated nutraceutical industry may lead healthcare providers and patients to underestimate the therapeutic potential of these medicines. We suggest three areas of emphasis for this field: First, vertical integration and embedding of traditional medicines into healthcare systems would subject them to appropriate regulation and evidence-based practice, as viable integrative implementation mode. Second, we offer a new Bradford-Hill-like framework for setting research priorities and evaluating efficacy, with the goal of rescuing potentially valuable therapies from the nutraceutical market and discrediting those that are pseudoscience. Third, data analytics pipelines offer new capacity to generate new types of TMS-inspired medicines that are rationally-designed based on integrated knowledge across cultures, and also provide an evaluative framework against which to test claims of fidelity and efficacy to TMS made for nutraceuticals. |*Data Science[MESH] |COVID-19/therapy[MESH] |Data Interpretation, Statistical[MESH] |Delivery of Health Care, Integrated/*organization & administration/*trends[MESH] |Humans[MESH] |Medicine[MESH] |Medicine, Traditional/*trends[MESH]Medicine in motion: Opportunities, challenges and data analytics-based(epmc).pdf DeepDyve Pubget Overpricing