Phase I Pharmacokinetics Study of Drug «COVID-globulin» (Specific Human Immunoglobulin Against COVID-19)
Bibliographic record
Abstract
Introductio n. Coronavirus infection is an acute viral disease with a predominant lesion of the upper respiratory tract caused by an RNA-containing virus of the Coronaviridae family. However, it is known that neutralizing antibodies play an important role in antiviral therapy because they effectively inhibit the reproduction of viruses and reduce the severity of the disease. Polyclonal antibodies contained in convalescent plasma are usually used as emergency therapy for emerging infectious diseases. In this aspect, the use of a human immunoglobulin G preparation containing specific antibodies to SARS-CoV-2 ("COVID-globulin") appears to be safer and more effective. Aim. The aim is pharmacokinetics study of drug "COVID-globulin" (specific human immunoglobulin against COVID-19, solution for infusions, not less than 160 anti-COVID units/mL (ACU/mL), JSC "NPO Microgen", owner of the registration certificate of JSC "Natsibio", Russia), in addition to standard therapy for the treatment of patients with middle-grade COVID-19. Materials and methods. The clinical and analytical stages of the study of the pharmacokinetics of drug "COVID-globulin", as well as the analysis of the safety and parameters of pharmacokinetics were carried as part of a clinical study of the safety, tolerability and pharmacokinetics of the drug immunoglobulin ("COVID-globulin"), not less than 160 anti-COVID units/mL (ACU/mL), JSC "NPO Microgen", owner of the registration certificate of JSC " Natsibio", Russia. Quantitative determination of antibody concentrations against SARS-CoV-2 was carried out by enzyme-linked immunosorbent assay using spectrophotometric detection in the visible range of the spectrum on an automatic plate enzyme-linked immunosorbent assay analyzer Lazurite (Dynex Technologies Inc., USA). The calculation of pharmacokinetic parameters was carried out using the Microsoft Excel package with an extension for pharmacokinetic analysis Boomer (Department of Pharmacokinetics and Drug Metabolism, Allergan, Irvine, CA 92606, USA). Results and discussion. No serious adverse events were reported in the study, and the only adverse event that resulted in a volunteer withdrawing from the study was not related to the use of the drug. The pharmacokinetic parameters of the drug "COVID-globulin" were calculated for two batches of drugs. The pharmacokinetics of the "COVID-globulin" (the content of antibodies to SARS-CoV-2 – 330 ACU/ml) was assessed on a sample of 8 volunteers. The maximum concentration of specific IgG antibodies to the SARS-CoV-2 virus was 25.46 ± 8.71 ACU/ml (Mean ± SD, where Mean is the arithmetic mean, SD is the standard deviation). The median value of the time to maximum concentration of specific IgG antibodies to the SARS-CoV-2 virus was 0.25 hours. Specific IgG antibodies to the SARS-CoV-2 virus were eliminated from blood plasma with a half-life value 266.89 ± 59.92 hours. The pharmacokinetics of the "COVID-globulin" (the content of antibodies to SARS-CoV-2 – 250 ACU/ml) was assessed on a sample of 15 volunteers. The maximum concentration of specific IgG antibodies to the SARS-CoV-2 virus was 20.93 ± 3.82 ACU/ml. The median value of the time to maximum concentration of specific IgG antibodies to the SARS-CoV-2 virus was 0.25 hours. Specific IgG antibodies to the SARS-CoV-2 virus were eliminated from blood plasma with a half-life value 295.56 ± 50.68 hours. Conclusion. According to the results of the study, the safety profile of the drug "COVID-globulin" is assessed as favorable. Based on the concentrations of specific IgG antibodies to the SARS-CoV-2 virus obtained during the analytical stage of the study, the main pharmacokinetic parameters were calculated, and the average pharmacokinetic profiles of the test drug "COVID-globulin" were plotted after a single injection. The results obtained were the basis for the subsequent phases of clinical trials of the drug "COVID-globulin".
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".