The emerging therapeutic potential of the oncolytic immunotherapeutic Pexa-Vec (JX-594)
Bibliographic record
Abstract
Oncolytic immunotherapeutics (OIs) are viruses designed to preferentially replicate in and lyse cancer cells, thereby triggering antitumor immunity. Numerous oncolytic platforms are currently in clinical development. Here we review preclinical and clinical experience with Pexa-Vec (pexastimogene devacirepvec, JX-594). Pexa-Vec is derived from a vaccinia vaccine strain that has been engineered to target cancer cells and express the therapeutic transgene granulocyte macrophage colony-stimulating factor (GM-CSF) in order to stimulate antitumor immunity. Key to its ability to target metastatic disease is the evolution of unique vaccinia virus characteristics that allow for effective systemic dissemination. Multiple mechanisms of action (MOA) for Pexa-Vec have been demonstrated in preclinical models and patients: 1) tumor cell infection and lysis, 2) antitumor immune response induction, and 3) tumor vascular disruption. This review will summarize data on the Pexa-Vec MOA as well as provide an overview of the Pexa-Vec clinical development program from multiple Phase I studies, Phase II studies in renal cell cancer and colorectal cancer, through Phase IIb clinical testing in patients with advanced hepatocellular carcinoma (primary liver cancer).
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".