Cell carriers for oncolytic viruses: current challenges and future directions
Bibliographic record
Abstract
The optimal route for clinical delivery of oncolytic viruses is thought to be systemic intravenous injection; however, the immune system is armed with several highly efficient mechanisms to remove pathogens from the circulatory system. To overcome the challenges faced in trying to delivery oncolytic viruses specifically to tumors via the bloodstream, carrier cells have been investigated to determine their suitability as delivery vehicles for systemic administration of oncolytic viruses. Cell carriers protect viruses from neutralization, one of the most limiting aspects of oncolytic virus interaction with the immune system. Cell carriers can also possess inherent tumor tropism, thus directing the delivery of the virus more specifically to a tumor. With preclinical studies already demonstrating the success and feasibility of this approach with multiple oncolytic viruses, clinical evaluation of cell-mediated delivery of viruses is on the horizon. Meanwhile, ongoing preclinical studies are aimed at identifying new cellular vehicles for oncolytic viruses and improving current promising cell carrier platforms.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".