Preliminary results from the randomized phase 2 study (1801 part 3B) of elraglusib in combination with gemcitabine/nab-paclitaxel (GnP) versus GnP alone in patients (pts) with previously untreated metastatic pancreatic ductal adenocarcinoma (mPDAC).
Bibliographic record
Abstract
4006 Background: Elraglusib (9-ING-41) is a first-in-class inhibitor of GSK-3ß, which may mediate drug resistance, EMT, and damaged DNA and tumor immune response in advanced cancer. In pancreatic cancer models in mice, elraglusib combined with chemotherapy enhanced anti-tumor effects and survival. In a single-arm clinical study, elraglusib/GnP showed antitumor activity and prolonged survival in pts with mPDAC. Methods: Pts with previously untreated mPDAC were randomized 2:1 to GnP plus elraglusib 9.3 mg/kg IV once weekly or GnP in an open-label phase 2 study. The primary endpoint was 1-yr OS in the primary analysis set. Upon study completion, mOS will be the primary endpoint once survival distributions are compared after the 12-month follow-up using log-rank analysis. Secondary endpoints included DCR, ORR, mPFS, and TEAEs/TRAEs. The planned sample size was 207 evaluable pts (130 for elraglusib/GnP and 77 for GnP), assuming 1-yr OS of 55% with elraglusib/GnP and 35% with GnP to achieve 80% power with a chi-square test at a 2-sided 5% α. For OS, nonparametric log-rank test was used with statistical significance at p-value < 0.048. Cytokine/chemokine correlative biomarker assays were performed. The study completed enrollment in February 2024. Results: As of November 15, 2024 (preliminary data cut-off date), the primary analysis set included 155 pts in the elraglusib/GnP arm and 78 pts in the GnP arm, with 52.8% males and 57.5% ECOG PS 1. Median (range) CA 19-9 levels were 1568 U/mL (1 to 381,904 U/mL) in the elraglusib/GnP arm and 1590 U/mL (2 to 501,000 IU/mL) in the GnP arm. The 1-yr OS rate was 43.6% with elraglusib/GnP vs 22.5% with GnP (z-test p = 0.002); the mOS was 9.3 mo with elraglusib/GnP vs 7.2 mo with GnP (HR, 0.63; log rank p = 0.016; see Table). 38.1% of pts on elraglusib/GnP and 19.2% on GnP are censored, with the majority at > 10 months OS. Several biomarkers appear to be predictive for OS including IFNβ and PD-L1. The most common TRAE with elraglusib/GnP was grade 1-2 transient visual impairment in > 60% of patients (vs 9% with GnP). Grade ≥3 TEAEs occurred in 89.7% of pts on elraglusib/GnP and 80.8% on GnP. Most common grade ≥3 TEAEs with elraglusib/GnP (vs GnP) were neutropenia 51.6% (vs 29.5%), anemia 24.5% (vs 29.5%), and fatigue 16.1% (vs 5.1%). Conclusions: The preliminary results showed a statistically significant benefit for 1-yr OS and mOS and favorable trends for ORR and DCR with elraglusib/GnP over GnP, with manageable safety profile. The mOS for GnP is lower relative to MPACT and NAPOLI-3 but comparable to recent real-world meta-analyses, explained by advanced disease burden and higher mortality rate in the first 4 months in our study. Topline analysis (April 2025) and correlative biomarker analysis predictive for OS will be presented. Clinical trial information: NCT03678883 . Preliminary efficacy results. Elraglusib/GnPn=155 GnPn=78 1-year OS, %z-test p=0.002 43.6 22.5 mOS, moHR=0.63; log-rank p=0.016 9.3 7.2 Events, n (%) 96 (61.9) 63 (80.8) mPFS, moHR=0.91; p=NS 5.6 4.9 Events, n (%) 128 (82.6) 70 (89.7) DCR, % 42.6 33.3 ORR, n (%) 43 (27.7) 16 (20.5)
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".