On-demand controlled release of docetaxel from a battery-less MEMS drug delivery device
Bibliographic record
Abstract
We report the development of a magnetically controlled MEMS device capable of on-demand release of defined quantities of an antiproliferative drug, docetaxel (DTX). Controlled release of DTX with a dosage suitable for the treatment of diabetic retinopathy has been achieved for 35 days. The device consists of a drug-loaded microreservoir (Ø6 mm ×∼550 μm), sealed by an elastic magnetic PDMS (polydimethylsiloxane) membrane (Ø6 mm × 40 μm) with a laser-drilled aperture (∼100 × 100 μm(2)). By applying a magnetic field, the magnetic PDMS membrane deforms, causing the discharge of the drug solution from the device. Controlled DTX release at a rate of 171 ± 16.7 ng per actuation interval has been achieved for 35 days using a 255 mT magnetic field. The background leakage of drug solution through the aperture was negligible at 0.053 ± 0.014 ng min(-1). The biological activity of the released drug was investigated using a cytotoxicity assay (cell apoptosis) for two cell lines, HUVEC (human umbilical vein endothelial cells) and PC3 (prostate cancer) cells. Reproducible release rates have been achieved and DTX within the PDMS MEMS reservoir maintains full pharmacological efficacy for more than two months. This device is a proof-of-concept development for targeted delivery of hydrophobic drugs such as DTX and other taxane-based agents that require accurate delivery in nanomolar concentrations.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 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".