Microneedle arrays for brain drug delivery: the potential of additive manufacturing
Bibliographic record
Abstract
For a long time, the treatment of brain diseases has been a significant challenge. Drug delivery to the brain has recently become one of the most challenging problems for patients with severe forms of central nervous system diseases. The blood–brain barrier (BBB) poses a significant challenge for drug delivery to the brain. While extensive efforts focus on finding materials to overcome the BBB for brain tumor treatment, it limits the penetration of chemotherapeutic drugs for the broader treatment of brain diseases. The oral method of drug administration has several drawbacks, such as the loss of drugs because of metabolism and gastrointestinal environmental issues. Besides, using the intravenous route to administer medicines has several disadvantages, including discomfort at the injection site, infection, bleeding, anxiety, and incompetence toward patients. Fabrication and development of microneedles to overcome the drawbacks mentioned above of traditional drug delivery methods may be a viable alternative. Drug delivery using microneedle arrays (MNAs) has recently been shown to be an effective method for delivering drugs to the brain. Different fabricating methods like three-dimensional printing could be used for the fabrication of personalized drug delivery systems, like MNAs, with precise control over spatiotemporal drug distribution. This article presents a review of using MNAs for drug delivery to the brain.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".