Trial reportCPT: pharmacometrics & systems pharmacology2022
PK/PD modeling links accelerated resolution of COVID-19-related clinical symptoms to SARS-CoV-2 viral load reduction in patients following treatment with Bamlanivimab alone or Bamlanivimab and Etesevimab together.
Trial report in CPT: pharmacometrics & systems pharmacology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
3 citing papers in PubMed, 4 citations in OpenAlex.
- Association between SARS-CoV-2 viral kinetics and clinical score evolution in hospitalized patients.CPT: pharmacometrics & systems pharmacology · 2023Trial
- PK/PD modeling links accelerated resolution of COVID-19-related clinical symptoms to SARS-CoV-2 viral load reduction in patients following treatment with Bamlanivimab alone or Bamlanivimab and Etesevimab together.CPT: pharmacometrics & systems pharmacology · 2022Trial
- Pharmacokinetic-pharmacodynamic modeling of a highly potent and broadly neutralizing anti-CD4 trimeric nanobody to inhibit HIV-1 infection.Microbiology spectrum · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The relationship between severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) viral load reduction and disease symptom resolution remains largely undefined for coronavirus disease 2019 (COVID-19). While the vaccine-derived immunity takes time to develop, neutralizing monoclonal antibodies offer immediate, passive immunity to patients with COVID-19. Bamlanivimab and etesevimab are two potent neutralizing monoclonal antibodies directed to the receptor binding domain of the spike protein of SARS-CoV-2. This study aims to describe the relationship between viral load and resolution of eight common COVID-19-related symptoms in patients following treatment with neutralizing monoclonal antibodies (bamlanivimab alone or bamlanivimab and etesevimab together), in a phase II clinical trial. Corresponding pharmacokinetics (PKs), viral load, and COVID-19-related symptom data were modeled using Nonlinear Mixed Effects Modeling to describe the time-course of eight COVID-19-related symptoms in an ordered categorical manner (none, mild, moderate, and severe), following administration of bamlanivimab or bamlanivimab and etesevimab together to participants with COVID-19. The PK/pharmacodynamic (PD) models characterized the exposure-viral load-symptom time course of the eight preselected COVID-19-related symptoms. Baseline viral load (BVL), change in viral load from baseline, and time since the onset of symptoms, demonstrated statistically significant effects on symptom score probabilities. Higher BVL generally indicated an increased probability of symptom severity. The severity of symptoms decreased over time, partially driven by the decrease in viral load. The effect of increasing time resulting in decreased severity of symptoms was over and above the effect of decreasing viral load. Administration of bamlanivimab alone or together with etesevimab results in a faster time to resolution of COVID-19-related symptoms compared to placebo.
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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.