First-in-Human Phase I Study of ABBV-838, an Antibody–Drug Conjugate Targeting SLAMF7/CS1 in Patients with Relapsed and Refractory Multiple Myeloma
Bibliographic record
Abstract
PURPOSE: ABBV-838 is an antibody-drug conjugate targeting a unique epitope of CD2 subset 1, a cell-surface glycoprotein expressed on multiple myeloma cells. This phase I/Ib first-in-human, dose-escalation study (trial registration ID: NCT02462525) evaluated the safety, pharmacokinetics, and preliminary activity of ABBV-838 in patients with relapsed and refractory multiple myeloma (RRMM). PATIENTS AND METHODS: Eligible patients (≥18 years) received ABBV-838 (3+3 design) intravenously starting from 0.6 mg/kg up to 6.0 mg/kg for 3-week dosing intervals (Q3W). Patients could continue ABBV-838 for up to 24 months. Assessment of alternate dosing intervals (Q1W and Q2W) was conducted in parallel. RESULTS: As of March 2017, 75 patients received at least one dose of ABBV-838. The most common any-grade treatment-emergent adverse events (TEAE) were neutropenia and anemia (28.0% each), fatigue (26.7%), and nausea (25.3%). Grade 3/4/5 TEAEs were reported in 73.3% of patients across all treatment groups; most common were neutropenia (20.0%), anemia (18.7%), and leukopenia (13.3%). Grade 3/4/5 ABBV-838-related TEAEs were reported by 40.0% of patients across all treatment groups. Overall, 4.0% of patients experienced TEAEs leading to death, none ABBV-838 related. The MTD was not reached; the selected recommended dose for the expansion cohort was 5.0 mg/kg Q3W. Pharmacokinetic analysis showed that exposure was approximately dose proportional. The overall response rate was 10.7%; very good partial responses and partial responses were achieved by 2 (2.7%) and 6 (8.0%) patients, respectively. CONCLUSIONS: These results demonstrate that ABBV-838 is safe and well-tolerated in patients with RRMM with a very limited efficacy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| 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".