Cooling-Triggered Release of Celecoxib from Implantable Alginate-Soluplus Composite Devices
Bibliographic record
Abstract
Currently, on-demand treatment of pain (both chronic and acute) is primarily achieved using opioids that are delivered systemically. Unfortunately, these drugs are highly addictive; over 5 people per hour die from opioid abuse in the US alone. A safer, nonsystemic mechanism for pain relief is therefore needed. Nonsteroidal anti-inflammatory drugs (NSAIDs) have been explored for this purpose; they are nonaddictive, provide excellent pain relief, and can be delivered locally to minimize dosage and systemic side effects. However, an on-demand release method is needed to make local delivery of these drugs a viable, convenient replacement for opioids; external stimulus-triggered release from an implantable depot is one approach. Stimuli such as heat, light, ultrasound, and RF electromagnetic radiation have been used to trigger release of various drugs from implantable drug depots; however, these require energy input and complex apparatus and are thus not comparable to the ease of oral administration. We propose localized cooling as a safe, convenient stimulus. As icepacks are already widely applied to temporarily ease local pain, introducing a drug delivery mechanism switched "ON" by cooling could enable long duration, enhanced pain relief triggered by a method with which patients are already familiar. Herein, we demonstrate that cooling-triggered release of NSAIDs can be achieved by leveraging the gel-to-sol transition exhibited by physically cross-linked thermoresponsive polymer hydrogels upon cooling below their lower critical solution temperature (LCST). We demonstrate and characterize cooling-triggered release in simulated body fluid, in cell culture, in explanted tissue, and in a live animal wound model. We show that hydrogels loaded with an NSAID (Celecoxib) can be combined with a nonthermoresponsive membrane material to create implantable devices that demonstrate up to a ∼40× increase in drug release rate upon mild cooling (29 °C) and that support multiple cycles of triggered release. These results demonstrate that cooling-triggered release of therapeutics is a promising concept that could allow patients to use a familiar method (applying an icepack to pain points) to achieve enhanced pain relief.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".