About: One of the many questions with respect to controlling the novel coronavirus pandemic is whether existing drugs can be re-purposed (re-positioned) for the prevention or treatment of Covid-19 - or for any future epidemic. The usefulness of existing approaches for re-purposing range from computational modeling to clinical trials. These are often time-consuming, resource intensive, and prone to failure. Proposed here is a new but simple concept that would capitalize on the opportunity presented by the on-going natural experiment involving the collection of data from epidemiological surveillance screening and diagnostic testing for clinical treatment. The objective would be to also collect for each Covid-19 case the patient's prior usage of existing therapeutic drugs. These drug usage data would be collected for several major test groups - those who test positive for active SARS-CoV-2 infection (using molecular methods) and those who test negative for current infection but also test positive for past infection (using serologic antibody tests). Patients from each of these groups would also be categorized with respect to where they resided on the spectrum of morbidities (from no or mild symptomology to severe). By comparing the distribution of normalized usage data for each drug within each group, drugs that are more associated with particular test groups could be revealed as having potential prophylactic, therapeutic, or contraindicated effects with respect to disease progression. These drugs could then be selected as candidates for further evaluation in fighting Covid-19. Also summarized are some of the numerous attributes, advantages, and limitations of the proposed concept, all pointing to the need for further discussion and evaluation.   Goto Sponge  NotDistinct  Permalink

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  • One of the many questions with respect to controlling the novel coronavirus pandemic is whether existing drugs can be re-purposed (re-positioned) for the prevention or treatment of Covid-19 - or for any future epidemic. The usefulness of existing approaches for re-purposing range from computational modeling to clinical trials. These are often time-consuming, resource intensive, and prone to failure. Proposed here is a new but simple concept that would capitalize on the opportunity presented by the on-going natural experiment involving the collection of data from epidemiological surveillance screening and diagnostic testing for clinical treatment. The objective would be to also collect for each Covid-19 case the patient's prior usage of existing therapeutic drugs. These drug usage data would be collected for several major test groups - those who test positive for active SARS-CoV-2 infection (using molecular methods) and those who test negative for current infection but also test positive for past infection (using serologic antibody tests). Patients from each of these groups would also be categorized with respect to where they resided on the spectrum of morbidities (from no or mild symptomology to severe). By comparing the distribution of normalized usage data for each drug within each group, drugs that are more associated with particular test groups could be revealed as having potential prophylactic, therapeutic, or contraindicated effects with respect to disease progression. These drugs could then be selected as candidates for further evaluation in fighting Covid-19. Also summarized are some of the numerous attributes, advantages, and limitations of the proposed concept, all pointing to the need for further discussion and evaluation.
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  • Therapy
  • Epidemiology
  • Clinical research
  • 2019 disasters in China
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