ArticleResults in physics2022
Forecasting of the efficiency of monoclonal therapy in the treatment of CoViD-19 induced by the Omicron variant of SARS-CoV2.
Article in Results in physics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 10 citations in OpenAlex.
- An overview on the treatments and prevention against COVID-19.Virology journal · 2023Review
- Combined Impact of Omicron Vaccination and Environmental Risk Exposure: A Thailand Case Study.Vaccines · 2023Article
- HIV and SARS-CoV-2 Co-Infection: From Population Study Evidence to In Vitro Studies.Life (Basel, Switzerland) · 2022Review
- COVID-19 Variants and Transfer Learning for the Emerging Stringency Indices.Neural processing letters · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
On November 26, 2021, the World Health Organization (WHO) announced a new variant of concern of SARS-CoV2 called Omicron. This variant has biological-functional characteristics such as to make it much faster in the infectious process so as to show an even more intense spread. Although many data are currently incomplete, it is possible to identify, based on the viral biochemical characteristics, a possible therapy consisting of a monoclonal antibody called Sotrovimab. The model proposed here is based on the mathematical analysis of the dynamics of action of this monoclonal antibody and two cell populations: the immune memory cells and the infected cells. Indeed, a delay exists during the physiological immune response and the response induced by administration of Sotrovimab. This manuscript presents that delay in a novel manner. The model is developed with the aid of information based on the chemical kinetics. The machine learning tools have been used to satisfy the criteria designed by the dynamical analysis. Regression learner tools of Python are used as the reverse engineering tools for the understanding of the balance in the mathematical model, maintained by the parameters and their corresponding intervals and thresholds set by the dynamical analysis.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.