Safety and Pharmacokinetics of Long‐Acting Monoclonal Antibodies Tixagevimab and Cilgavimab (AZD7442) in a China Phase 2 Study and Evaluation of Asian Race Effect
Bibliographic record
Abstract
Safety, pharmacokinetics, and impact of race of pharmacokinetics on monoclonal antibodies tixagevimab and cilgavimab (AZD7442) were assessed in Chinese adult participants in a Phase 2, randomized, double-blind, placebo-controlled trial. In total, 272 participants were randomized 3:1 to a single intravenous dose of 600 mg AZD7442 or placebo and followed for 451 days. Mean participant age was 34.2 years, 5.9% were aged greater than 60 years, and 69.1% were male. Adverse events (AEs) occurred in 72.8% and 80.0% of participants with AZD7442 and placebo, respectively; most were mild or moderate in severity. Serious AEs were reported in 3.0% and 4.3% of participants with AZD7442 and placebo, respectively. No AEs of special interest, infusion-related reactions, or deaths occurred. Maximum serum concentrations of tixagevimab and cilgavimab were rapidly achieved following infusion, then declined through Day 361. Mean half-lives were 85 days for tixagevimab and 80 days for cilgavimab. AZD7442 recipients exhibited greater than 4-fold neutralizing antibody titer increases versus baseline at Day 8, which then declined through Day 361. Among AZD7442 recipients, 20.8% were treatment-emergent antidrug antibody positive. Asian race had no clinically significant impact on AZD7442 pharmacokinetics. Overall, intravenous 600 mg AZD7442 was well tolerated in Chinese adult participants. AZD7442 pharmacokinetics were similar in Asian and non-Asian participants. ClinicalTrials.gov identifier: NCT05184062.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".