Osmotically driven drug delivery through remote-controlled magnetic nanocomposite membranes
Why this work is in the frame
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Bibliographic record
Abstract
Implantable drug delivery systems can provide long-term reliability, controllability, and biocompatibility, and have been used in many applications, including cancer pain and non-malignant pain treatment. However, many of the available systems are limited to zero-order, inconsistent, or single burst event drug release. To address these limitations, we demonstrate prototypes of a remotely operated drug delivery device that offers controllability of drug release profiles, using osmotic pumping as a pressure source and magnetically triggered membranes as switchable on-demand valves. The membranes are made of either ethyl cellulose, or the proposed stronger cellulose acetate polymer, mixed with thermosensitive poly(N-isopropylacrylamide) hydrogel and superparamagnetic iron oxide particles. The prototype devices' drug diffusion rates are on the order of 0.5-2 μg/h for higher release rate designs, and 12-40 ng/h for lower release rates, with maximum release ratios of 4.2 and 3.2, respectively. The devices exhibit increased drug delivery rates with higher osmotic pumping rates or with magnetically increased membrane porosity. Furthermore, by vapor deposition of a cyanoacrylate layer, a drastic reduction of the drug delivery rate from micrograms down to tens of nanograms per hour is achieved. By utilizing magnetic membranes as the valve-control mechanism, triggered remotely by means of induction heating, the demonstrated drug delivery devices benefit from having the power source external to the system, eliminating the need for a battery. These designs multiply the potential approaches towards increasing the on-demand controllability and customizability of drug delivery profiles in the expanding field of implantable drug delivery systems, with the future possibility of remotely controlling the pressure source.
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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 | 0.000 |
| 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) | 0.000 | 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 it