What are the latest covid drugs and treatments?

Looi, Mun-Keat

doi:10.1136/bmj.p872

Cited by 4 publications

(3 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Third, a rule-based approach was used to increase credibility by selecting text with conclusive descriptions in the abstract. According to these criteria, the top 3 drugs ranked by the sum of the probability scores included ritonavir, dexamethasone, and baricitinib, which are currently widely used and validated in the treatment of COVID-19 [ 81 ].…”

Section: Discussionmentioning

confidence: 99%

Large-Scale Biomedical Relation Extraction Across Diverse Relation Types: Model Development and Usability Study on COVID-19

Zhang,

Fang,

et al. 2023

J Med Internet Res

View full text Add to dashboard Cite

Background Biomedical relation extraction (RE) is of great importance for researchers to conduct systematic biomedical studies. It not only helps knowledge mining, such as knowledge graphs and novel knowledge discovery, but also promotes translational applications, such as clinical diagnosis, decision-making, and precision medicine. However, the relations between biomedical entities are complex and diverse, and comprehensive biomedical RE is not yet well established. Objective We aimed to investigate and improve large-scale RE with diverse relation types and conduct usability studies with application scenarios to optimize biomedical text mining. Methods Data sets containing 125 relation types with different entity semantic levels were constructed to evaluate the impact of entity semantic information on RE, and performance analysis was conducted on different model architectures and domain models. This study also proposed a continued pretraining strategy and integrated models with scripts into a tool. Furthermore, this study applied RE to the COVID-19 corpus with article topics and application scenarios of clinical interest to assess and demonstrate its biological interpretability and usability. Results The performance analysis revealed that RE achieves the best performance when the detailed semantic type is provided. For a single model, PubMedBERT with continued pretraining performed the best, with an F1-score of 0.8998. Usability studies on COVID-19 demonstrated the interpretability and usability of RE, and a relation graph database was constructed, which was used to reveal existing and novel drug paths with edge explanations. The models (including pretrained and fine-tuned models), integrated tool (Docker), and generated data (including the COVID-19 relation graph database and drug paths) have been made publicly available to the biomedical text mining community and clinical researchers. Conclusions This study provided a comprehensive analysis of RE with diverse relation types. Optimized RE models and tools for diverse relation types were developed, which can be widely used in biomedical text mining. Our usability studies provided a proof-of-concept demonstration of how large-scale RE can be leveraged to facilitate novel research.

show abstract

Section: Discussionmentioning

confidence: 99%

Large-Scale Biomedical Relation Extraction Across Diverse Relation Types: Model Development and Usability Study on COVID-19

Zhang,

Fang,

et al. 2023

J Med Internet Res

View full text Add to dashboard Cite

show abstract

“…“I think we’re still seeing a mixture of different types of products in regard to the immunomodulation type,” she says. “We have corticosteroids, IL-6 receptor tocilizumab, and then Janus kinase inhibitors, baricitinib 1. If we can really improve access to those and get clinicians to integrate them into covid-19 care pathways for severe and critical cases in hospitals, I think that would be a big advancement.”…”

Section: What New Treatments or Approaches Are On The Horizon?mentioning

confidence: 99%

What is the future for covid drugs and treatments?

Looi¹

2023

BMJ

Self Cite

View full text Add to dashboard Cite

show abstract

“…Looking to the future of covid treatments, the focus is not so much on the “new” as on continuing current research to improve access to drugs we already know work (doi:10.1136/bmj.p872). 6 This is not to rule out the need for new drugs, especially antivirals. For patients with long covid, in particular, substantially more progress is needed.…”

mentioning

confidence: 99%