Organ-on-a-Chip Platforms for Drug Delivery and Cell Characterization: A Review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Developments in micro-and nanofluidic technologies have led to new kinds of cell culture and screening systems that are collectively termed organ-on-a-chip systems. Organ-on-a-chip systems are in vitro microfabricated devices that mimic dynamic interactions of in vivo microenvironments. In addition to existing two-dimensional and three-dimensional tissues, organ-on-a-chip systems can mimic the biomechanical and biochemical microenvironments of in vivo tissues as well as the interactional effects of the microenvironments on cell and tissue functions. Owing to those features, organ-ona-chip systems have become excellent platforms for drug screening and delivery tests. In this review, specific examples of organ-on-a-chip devices and their applications in tissue engineering and drug delivery tests are presented. The utility and performance of stateof-the-art organ-on-a-chip systems, including lung-on-a-chip, heart-on-a-chip, vessel-ona-chip, liver-on-a-chip, and tumor-on-a-chip, are also covered in this review. Limitations of conventional systems, basic fabrication processes for organ-on-a-chip devices, and future prospects of organ-on-a-chip systems are discussed.
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.
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) | 0.001 | 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