Alternative Strategies for Delivering Immunotherapeutics Targeting the PD-1/PD-L1 Immune Checkpoint in Cancer
Bibliographic record
Abstract
T cells activates downstream signaling pathways that culminate in T cell exhaustion and/or apoptosis. Physiologically, these immunosuppressive effects exist to prevent autoimmunity, but cancer cells exploit this pathway by overexpressing PD-L1 to facilitate immune escape. Intravenously (IV) administered immune checkpoint inhibitors (ICIs) that block the interaction between PD-1/PD-L1 have achieved great success in reversing T cell exhaustion and promoting tumor regression in various malignancies. However, these ICIs can cause immune-related adverse events (irAEs) due to off-tumor toxicities which limits their therapeutic potential. Therefore, considerable effort has been channeled into exploring alternative delivery strategies that enhance tumor-directed delivery of PD-1/PD-L1 ICIs and reduce irAEs. Here, we briefly describe PD-1/PD-L1-targeted cancer immunotherapy and associated irAEs. We then provide a detailed review of alternative delivery approaches, including locoregional (LDD)-, oncolytic virus (OV)-, nanoparticle (NP)-, and ultrasound and microbubble (USMB)-mediated delivery that are currently under investigation for enhancing tumor-specific delivery to minimize toxic off-tumor effects. We conclude with a commentary on key challenges associated with these delivery methods and potential strategies to mitigate them.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".