Ultrasound-triggered drug delivery: recent developments and opportunities
Bibliographic record
Abstract
While ultrasound-based medical imaging is widely used in clinics, ultrasound-triggered drug delivery represents an emerging modality that takes advantage of the high tissue penetrability, general safety, and high clinical accessibility of ultrasound to solve key challenges around localized drug delivery. In this review, we analyze emerging trends in the design of drug delivery vehicles activated using different ultrasound effects ranging from cavitation, mechanical stimulation, localized heating, reactive oxygen species generation, localized gas generation, and/or penetration enhancement. In particular, we focus on vehicle designs that enable delayed burst release, sustained release, and pulsatile on-off release of drugs locally at the targeted ultrasound site, each of which has direct applications for treating specific diseases. Vehicles in which ultrasound-mediated drug release kinetics control is synergistically coupled with other therapeutic benefits of ultrasound are highlighted. Finally, we discuss key barriers to the practical translation of ultrasound-triggered drug delivery vehicles into the clinic, aiming to motivate the design of scalable and reproducible ultrasound-triggered drug delivery vehicles that can have real-world patient impact.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".