A Drug-Eluting Injectable NanoGel for Localized Delivery of Anticancer Drugs to Solid Tumors
Bibliographic record
Abstract
Systemically administered chemotherapy reduces the efficiency of the anticancer agent at the target tumor tissue and results in distributed drug to non-target organs, inducing negative side effects commonly associated with chemotherapy and necessitating repeated administration. Injectable hydrogels present themselves as a potential platform for non-invasive local delivery vehicles that can serve as a slow-releasing drug depot that fills tumor vasculature, tissue, or resection cavities. Herein, we have systematically formulated and tested an injectable shear-thinning hydrogel (STH) with a highly manipulable release profile for delivering doxorubicin, a common chemotherapeutic. By detailed characterization of the STH physical properties and degradation and release dynamics, we selected top candidates for testing in cancer models of increasing biomimicry. Two-dimensional cell culture, tumor-on-a-chip, and small animal models were used to demonstrate the high anticancer potential and reduced systemic toxicity of the STH that exhibits long-term (up to 80 days) doxorubicin release profiles for treatment of breast cancer and glioblastoma. The drug-loaded STH injected into tumor tissue was shown to increase overall survival in breast tumor- and glioblastoma-bearing animal models by 50% for 22 days and 25% for 52 days, respectively, showing high potential for localized, less frequent treatment of oncologic disease with reduced dosage requirements.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".