Microphysiological lung models to evaluate the safety of new pharmaceutical modalities: a biopharmaceutical perspective
Bibliographic record
Abstract
The lung is a complex organ; it is both the initial barrier for inhaled agents and the site of metabolism and therapeutic effect for a subset of systemically administered drugs. Comprised of more than 40 cell types that are responsible for various important functions, the lung's complexity contributes to the subsequent challenges in developing complex in vitro co-culture models (also called microphysiological systems (MPS), complex in vitro models or organs-on-a-chip). Although there are multiple considerations and limitations in the development and qualification of such in vitro systems, MPS exhibit great promise in the fields of pharmacology and toxicology. Successful development and implementation of MPS models may enable mechanistic bridging between non-clinical species and humans, and increase clinical relevance of safety endpoints, while decreasing overall animal use. This article summarizes, from a biopharmaceutical industry perspective, essential elements for the development and qualification of lung MPS models. Its purpose is to guide MPS developers and manufacturers to expedite MPS utilization for safety assessment in the biopharmaceutical industry.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".