Inhalable Nanomaterial Discoveries for Lung Cancer Therapy: A Review
Bibliographic record
Abstract
Lung cancer remains one of the most common and deadliest forms of cancer worldwide despite notable advancements in its management. Conventional treatments, such as chemotherapy, often have limitations in effectively targeting cancer cells, which frequently lead to off-target side effects. In this context, the pulmonary delivery of inhalable nanomaterials offers the advantages of being rapid, efficient, and target-specific, with minimal systemic side effects. This concise review summarizes the basic research and clinical translation of inhalable nanomaterials for the treatment of lung cancer. We also provide insights into the latest advances in pulmonary drug delivery systems, focusing on various types of pulmonary devices and nanomaterials. Furthermore, this paper discusses significant challenges in translating the discoveries of inhalable nanomaterials into clinical care for lung cancer and shares strategies to overcome these issues.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".