First-in-human study of an EGFRvIII x CD3 T cell bispecific antibody in the treatment of newly diagnosed glioblastoma
Bibliographic record
Abstract
Background: This first-in-human study evaluated EGFRvIII × CD3 TCB, a novel T cell bispecific antibody, in patients with newly diagnosed EGFRvIII-positive glioblastoma. Methods: Patients with newly diagnosed glioblastoma received escalating doses of EGFRvIII × CD3 TCB following chemoradiation. The primary objectives were to evaluate safety/tolerability and define the maximum tolerated dose (MTD); secondary objectives included pharmacokinetics (PK), immunogenicity, pharmacodynamics, and clinical activity. Results: Thirty-six patients were enrolled, 32 with unmethylated and 4 with methylated MGMT promoter. EGFRvIII × CD3 TCB doses ranged from 0.004 to 10 mg Q3W, administered either on a flat or step-up dose schedule. One DLT occurred (grade 3 seizure). The MTD was not reached. Most adverse events (AEs) were of grade 1-2 severity, with headache being the most common treatment-related AE (22%). EGFRvIII × CD3 TCB showed dose-proportional PK in serum and cerebrospinal fluid (CSF), with a CSF/serum ratio of 0.08. At the highest dose tested, 10 mg Q3W, maximum serum concentrations remained 6-fold below the lower boundary of the predicted anticipated therapeutic dose. Conclusions: The administration of EGFRvIII × CD3 TCB in a maintenance setting, following standard of care treatment, was safe and well tolerated up to the highest tested dose of 10 mg Q3W. However, evidence of efficacy was not observed at the evaluated doses, suggesting that a study of higher dose levels may be warranted.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".