OVATION-2: A randomized phase I/II study evaluating the safety and efficacy of IMNN-001 (IL-12 gene therapy) with neo/adjuvant chemotherapy in patients newly-diagnosed with advanced epithelial ovarian cancer
Bibliographic record
Abstract
OBJECTIVE: OVATION-2, a randomized, controlled, open label phase 1/2 study, evaluated the safety and efficacy of IMNN-001, an IL-12 immune gene therapy, with neo/adjuvant chemotherapy (N/ACT) compared to N/ACT in newly-diagnosed advanced epithelial ovarian cancer (EOC). METHODS: IMNN-001 is an immunotherapeutic nanoparticle comprising a DNA plasmid encoding the IL-12 gene encased in a lipopolymer. High-grade EOC patients were randomized 1:1 to carboplatin/paclitaxel IV every 21 days for 3 cycles, before and after interval debulking surgery (IDS) or to intraperitoneal (IP) IMNN-001, given weekly concurrently with chemotherapy for 8 weeks before and 9 weeks after IDS. RESULTS: 54 and 58 patients with predominantly Stage IIIC/IV EOC were evaluated in the control and experimental arm, respectively. Primary endpoints were safety and PFS. Overall, the experimental arm was well tolerated with gastrointestinal and cytopenias as the most common TEAEs with no CRS or elevated risk of immune events. PFS was 14.9 months (mo) for the experimental arm vs 11.9 mo; HR 0.79 (95 % CI: 0.51-1.23). Secondary endpoints included OS (46.0 mo for experimental arm vs 33.0 mo; HR 0.69 (CI: 0.40-1.19)) and surgical response R0 rate (64.6 % experimental arm vs 52.1 %). For patients who received PARPi maintenance, PFS was 33.8 mo vs 22.1 mo; HR 0.80 (CI: 0.31-2.12) and OS was NE vs 37.1 mo with a HR of 0.38 (CI: 0.13-1.06) both favoring the experimental arm. CONCLUSION: The addition of IMNN-001 to N/ACT shows a promising numerical 13-mo benefit on survival with an acceptable safety profile in patients with newly-diagnosed advanced EOC.
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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) | 0.002 | 0.001 |
| 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".