LIVIVO - The Search Portal for Life Sciences

zur deutschen Oberfläche wechseln
Advanced search

Search results

Result 1 - 3 of total 3

Search options

  1. Article ; Online: The Anatomy of the SARS-CoV-2 Biomedical Literature: Introducing the CovidX Network Algorithm for Drug Repurposing Recommendation.

    Gates, Lyndsey Elaine / Hamed, Ahmed Abdeen

    Journal of medical Internet research

    2020  Volume 22, Issue 8, Page(s) e21169

    Abstract: Background: Driven by the COVID-19 pandemic and the dire need to discover an antiviral drug, we explored the landscape of the SARS-CoV-2 biomedical publications to identify potential treatments.: Objective: The aims of this study are to identify off- ... ...

    Abstract Background: Driven by the COVID-19 pandemic and the dire need to discover an antiviral drug, we explored the landscape of the SARS-CoV-2 biomedical publications to identify potential treatments.
    Objective: The aims of this study are to identify off-label drugs that may have benefits for the coronavirus disease pandemic, present a novel ranking algorithm called CovidX to recommend existing drugs for potential repurposing, and validate the literature-based outcome with drug knowledge available in clinical trials.
    Methods: To achieve such objectives, we applied natural language processing techniques to identify drugs and linked entities (eg, disease, gene, protein, chemical compounds). When such entities are linked, they form a map that can be further explored using network science tools. The CovidX algorithm was based upon a notion that we called "diversity." A diversity score for a given drug was calculated by measuring how "diverse" a drug is calculated using various biological entities (regardless of the cardinality of actual instances in each category). The algorithm validates the ranking and awards those drugs that are currently being investigated in open clinical trials. The rationale behind the open clinical trial is to provide a validating mechanism of the PubMed results. This ensures providing up to date evidence of the fast development of this disease.
    Results: From the analyzed biomedical literature, the algorithm identified 30 possible drug candidates for repurposing, ranked them accordingly, and validated the ranking outcomes against evidence from clinical trials. The top 10 candidates according to our algorithm are hydroxychloroquine, azithromycin, chloroquine, ritonavir, losartan, remdesivir, favipiravir, methylprednisolone, rapamycin, and tilorone dihydrochloride.
    Conclusions: The ranking shows both consistency and promise in identifying drugs that can be repurposed. We believe, however, the full treatment to be a multifaceted, adjuvant approach where multiple drugs may need to be taken at the same time.
    MeSH term(s) Antiviral Agents/pharmacology ; Antiviral Agents/therapeutic use ; Betacoronavirus/pathogenicity ; COVID-19 ; Coronavirus Infections/drug therapy ; Drug Repositioning/methods ; Humans ; Hydroxychloroquine/pharmacology ; Hydroxychloroquine/therapeutic use ; Pandemics ; Pneumonia, Viral/drug therapy ; SARS-CoV-2 ; COVID-19 Drug Treatment
    Chemical Substances Antiviral Agents ; Hydroxychloroquine (4QWG6N8QKH)
    Keywords covid19
    Language English
    Publishing date 2020-08-20
    Publishing country Canada
    Document type Journal Article
    ZDB-ID 2028830-X
    ISSN 1438-8871 ; 1438-8871
    ISSN (online) 1438-8871
    ISSN 1438-8871
    DOI 10.2196/21169
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

  2. Article: The Anatomy of the SARS-CoV-2 Biomedical Literature: Introducing the CovidX Network Algorithm for Drug Repurposing Recommendation

    Gates, Lyndsey Elaine / Hamed, Ahmed Abdeen

    J Med Internet Res

    Abstract: BACKGROUND: Driven by the COVID-19 pandemic and the dire need to discover an antiviral drug, we explored the landscape of the SARS-CoV-2 biomedical publications to identify potential treatments. OBJECTIVE: The aims of this study are to identify off-label ...

    Abstract BACKGROUND: Driven by the COVID-19 pandemic and the dire need to discover an antiviral drug, we explored the landscape of the SARS-CoV-2 biomedical publications to identify potential treatments. OBJECTIVE: The aims of this study are to identify off-label drugs that may have benefits for the coronavirus disease pandemic, present a novel ranking algorithm called CovidX to recommend existing drugs for potential repurposing, and validate the literature-based outcome with drug knowledge available in clinical trials. METHODS: To achieve such objectives, we applied natural language processing techniques to identify drugs and linked entities (eg, disease, gene, protein, chemical compounds). When such entities are linked, they form a map that can be further explored using network science tools. The CovidX algorithm was based upon a notion that we called "diversity." A diversity score for a given drug was calculated by measuring how "diverse" a drug is calculated using various biological entities (regardless of the cardinality of actual instances in each category). The algorithm validates the ranking and awards those drugs that are currently being investigated in open clinical trials. The rationale behind the open clinical trial is to provide a validating mechanism of the PubMed results. This ensures providing up to date evidence of the fast development of this disease. RESULTS: From the analyzed biomedical literature, the algorithm identified 30 possible drug candidates for repurposing, ranked them accordingly, and validated the ranking outcomes against evidence from clinical trials. The top 10 candidates according to our algorithm are hydroxychloroquine, azithromycin, chloroquine, ritonavir, losartan, remdesivir, favipiravir, methylprednisolone, rapamycin, and tilorone dihydrochloride. CONCLUSIONS: The ranking shows both consistency and promise in identifying drugs that can be repurposed. We believe, however, the full treatment to be a multifaceted, adjuvant approach where multiple drugs may need to be taken at the same time.
    Keywords covid19
    Publisher WHO
    Document type Article
    Note WHO #Covidence: #690513
    Database COVID19

    Kategorien

  3. Article ; Online: The Anatomy of the SARS-CoV-2 Biomedical Literature

    Gates, Lyndsey Elaine / Hamed, Ahmed Abdeen

    Journal of Medical Internet Research, Vol 22, Iss 8, p e

    Introducing the CovidX Network Algorithm for Drug Repurposing Recommendation

    2020  Volume 21169

    Abstract: BackgroundDriven by the COVID-19 pandemic and the dire need to discover an antiviral drug, we explored the landscape of the SARS-CoV-2 biomedical publications to identify potential treatments. ObjectiveThe aims of this study are to identify off-label ... ...

    Abstract BackgroundDriven by the COVID-19 pandemic and the dire need to discover an antiviral drug, we explored the landscape of the SARS-CoV-2 biomedical publications to identify potential treatments. ObjectiveThe aims of this study are to identify off-label drugs that may have benefits for the coronavirus disease pandemic, present a novel ranking algorithm called CovidX to recommend existing drugs for potential repurposing, and validate the literature-based outcome with drug knowledge available in clinical trials. MethodsTo achieve such objectives, we applied natural language processing techniques to identify drugs and linked entities (eg, disease, gene, protein, chemical compounds). When such entities are linked, they form a map that can be further explored using network science tools. The CovidX algorithm was based upon a notion that we called “diversity.” A diversity score for a given drug was calculated by measuring how “diverse” a drug is calculated using various biological entities (regardless of the cardinality of actual instances in each category). The algorithm validates the ranking and awards those drugs that are currently being investigated in open clinical trials. The rationale behind the open clinical trial is to provide a validating mechanism of the PubMed results. This ensures providing up to date evidence of the fast development of this disease. ResultsFrom the analyzed biomedical literature, the algorithm identified 30 possible drug candidates for repurposing, ranked them accordingly, and validated the ranking outcomes against evidence from clinical trials. The top 10 candidates according to our algorithm are hydroxychloroquine, azithromycin, chloroquine, ritonavir, losartan, remdesivir, favipiravir, methylprednisolone, rapamycin, and tilorone dihydrochloride. ConclusionsThe ranking shows both consistency and promise in identifying drugs that can be repurposed. We believe, however, the full treatment to be a multifaceted, adjuvant approach where multiple drugs may need to be taken at the same time.
    Keywords Computer applications to medicine. Medical informatics ; R858-859.7 ; Public aspects of medicine ; RA1-1270
    Language English
    Publishing date 2020-08-01T00:00:00Z
    Publisher JMIR Publications
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    More links

    Kategorien

To top