Hepatic organoids for microfluidic drug screening
Bibliographic record
Abstract
We introduce the microfluidic organoids for drug screening (MODS) platform, a digital microfluidic system that is capable of generating arrays of individually addressable, free-floating, three-dimensional hydrogel-based microtissues (or 'organoids'). Here, we focused on liver organoids, driven by the need for early-stage screening methods for hepatotoxicity that enable a "fail early, fail cheaply" strategy in drug discovery. We demonstrate that arrays of hepatic organoids can be formed from co-cultures of HepG2 and NIH-3T3 cells embedded in hydrogel matrices. The organoids exhibit fibroblast-dependent contractile behaviour, and their albumin secretion profiles and cytochrome P450 3A4 activities are better mimics of in vivo liver tissue than comparable two-dimensional cell culture systems. As proof of principle for screening, MODS was used to generate and analyze the effects of a dilution series of acetaminophen on apoptosis and necrosis. With further development, we propose that the MODS platform may be a cost-effective tool in a "fail early, fail cheaply" paradigm of drug development.
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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".