Evidence map›Paper›PMID 38534112›Full record

ArticleAntimicrobial agents and chemotherapy2024

Accelerating therapeutics development during a pandemic: population pharmacokinetics of the long-acting antibody combination AZD7442 (tixagevimab/cilgavimab) in the prophylaxis and treatment of COVID-19.

Lindsay E Clegg, Oleg Stepanov, Henning Schmidt, Weifeng Tang, Huixia Zhang, Chris Webber, Taylor S Cohen, Mark T Esser, Mats Någård

Open access · hybridAbstract read
In one paragraph

Article in Antimicrobial agents and chemotherapy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
5.4field-weighted citation impact, top 3% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 14 citations in OpenAlex.

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  9. Molecular mechanisms of SARS-CoV-2 entry: implications for biomedical strategies.Microbiology and molecular biology reviews : MMBR · 2025
    Review
  10. Article
  11. Serum AZD7442 (tixagevimab-cilgavimab) concentrations andClinical & translational immunology · 2024
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 2 institutions in 2 countries.

Lindsay E Clegg *Clinical Pharmacology and Quantitative Pharmacology, Clinical Pharmacology & Safety Sciences, R&D, AstraZeneca, Gaithersburg, Maryland, USA.ORCID 0000-0001-8558-9341
Oleg Stepanov *Clinical Pharmacology and Quantitative Pharmacology, Clinical Pharmacology & Safety Sciences, R&D, AstraZeneca, Cambridge, United Kingdom.
Henning SchmidtIntiQuan GmBH, Basel, Switzerland.
Weifeng TangClinical Pharmacology and Quantitative Pharmacology, Clinical Pharmacology & Safety Sciences, R&D, AstraZeneca, Gaithersburg, Maryland, USA.
Huixia ZhangClinical Pharmacology and Quantitative Pharmacology, Clinical Pharmacology & Safety Sciences, R&D, AstraZeneca, Gaithersburg, Maryland, USA.
Chris WebberClinical Development, Vaccines and Immune Therapies, BioPharmaceuticals R&D, AstraZeneca, Cambridge, United Kingdom.
Taylor S CohenVaccines & Immune Therapies, BioPharmaceuticals R&D, AstraZeneca, Gaithersburg, Maryland, USA.
Mark T EsserVaccines & Immune Therapies, BioPharmaceuticals R&D, AstraZeneca, Gaithersburg, Maryland, USA.
Mats NågårdClinical Pharmacology and Quantitative Pharmacology, Clinical Pharmacology & Safety Sciences, R&D, AstraZeneca, Gaithersburg, Maryland, USA.
AstraZeneca (United States) · USAstraZeneca (United Kingdom) · GB

Funding

AstraZeneca (AstraZeneca PLC) N/A
6 · The paper itself

Abstract

AZD7442 is a combination of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-neutralizing antibodies, tixagevimab and cilgavimab, developed for pre-exposure prophylaxis (PrEP) and treatment of coronavirus disease 2019 (COVID-19). Using data from eight clinical trials, we describe a population pharmacokinetic (popPK) model of AZD7442 and show how modeling of "interim" data accelerated decision-making during the COVID-19 pandemic. The final model was a two-compartmental distribution model with first-order absorption and elimination, including standard allometric exponents for the effect of body weight on clearance and volume. Other covariates included were as follows: sex, age >65 years, body mass index ≥30 kg/m

Indexed as

Antibodies, Monoclonal, HumanizedCOVID-19COVID-19 Drug TreatmentSARS-CoV-2AdolescentAdultAgedAntibodies, NeutralizingAntiviral AgentsFemaleHumansMaleMiddle AgedYoung AdultAntibodies, Monoclonal, HumanizedAntibodies, NeutralizingAntiviral AgentsAZD7442cilgavimabCOVID-19monoclonal antibodiespopulation pharmacokineticsSARS-CoV-2tixagevimab

Identifiers

PMID38534112
PMCPMC11064475
OpenAlexW4393223739

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.