Beyond Polydimethylsiloxane: Alternative Materials for Fabrication of Organ-on-a-Chip Devices and Microphysiological Systems
Bibliographic record
Abstract
Polydimethylsiloxane (PDMS) is the predominant material used for organ-on-a-chip devices and microphysiological systems (MPSs) due to its ease-of-use, elasticity, optical transparency, and inexpensive microfabrication. However, the absorption of small hydrophobic molecules by PDMS and the limited capacity for high-throughput manufacturing of PDMS-laden devices severely limit the application of these systems in personalized medicine, drug discovery, in vitro pharmacokinetic/pharmacodynamic (PK/PD) modeling, and the investigation of cellular responses to drugs. Consequently, the relatively young field of organ-on-a-chip devices and MPSs is gradually beginning to make the transition to alternative, nonabsorptive materials for these crucial applications. This review examines some of the first steps that have been made in the development of organ-on-a-chip devices and MPSs composed of such alternative materials, including elastomers, hydrogels, thermoplastic polymers, and inorganic materials. It also provides an outlook on where PDMS-alternative devices are trending and the obstacles that must be overcome in the development of versatile devices based on alternative materials to PDMS.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".