‘Smart’ Magnetic Nanocomposite Hydrogels for Drug Delivery
Bibliographic record
Abstract
The capability of precisely controlling the kinetics of therapeutic delivery at the optimal location and rate for a given patient would have great potential to improve health and well-being in a range of current drug therapies (insulin, chemotherapeutics, vaccines, etc.). Indeed, if successfully developed, locally administered injectable drug delivery vehicles capable of remotely-triggered release would be the gold standard for many treatments. Multiple injectable nanocomposites have been investigated for this purpose that are generally comprised of a thermosensitive polymeric material and superparamagnetic iron oxide nanoparticles (SPIONs). SPIONs generate heat when exposed remote alternating magnetic fields (AMFs), and the transfer of this heat to thermosensitive polymers can be used to control the release of therapeutics. Ideally, these systems would be capable of returning to their original state and basal release rate when the external AMF trigger is removed. Several novel injectable nanocomposite materials that explore interactions between SPIONs and thermosensitive polymers to mediate drug release, from the macroscale to the nanoscale, were developed and demonstrated to be capable of remotely-triggered, AMF-mediated enhanced release. The macroscale magnetic nanocomposites have thermosensitive hydrogel and/or microgel components that regulate release based on the heat produced from SPIONs in response to an external AMF. On the millimeter-scale, a microinjection system capable of producing thermosensitive hydrogel beads that could potentially incorporate SPIONs is described. On the nanoscale, nanoparticles with a glass transition temperature and thermosensitive microgels are combined with SPIONs and investigated for their remote, AMF-mediated release characteristics. The engineered macroscale and nanoscale systems are capable of up to ~4:1 and ~7:1 enhancements in release due to an AMF application, respectively, compared to the basal release rate. Collectively, these nanocomposites represent a promising stride towards improved remote-actuation of drug release and a stepping stone for future attempts at precisely controlling the site and kinetics of drug release.
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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) | 0.002 | 0.001 |
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".