A roadmap for developing and engineering <i>in vitro</i> pulmonary fibrosis models
Bibliographic record
Abstract
Idiopathic pulmonary fibrosis (IPF) is a severe form of pulmonary fibrosis. IPF is a fatal disease with no cure and is challenging to diagnose. Unfortunately, due to the elusive etiology of IPF and a late diagnosis, there are no cures for IPF. Two FDA-approved drugs for IPF, nintedanib and pirfenidone, slow the progression of the disease, yet fail to cure or reverse it. Furthermore, most animal models have been unable to completely recapitulate the physiology of human IPF, resulting in the failure of many drug candidates in preclinical studies. In the last few decades, the development of new IPF drugs focused on changes at the cellular level, as it was believed that the cells were the main players in IPF development and progression. However, recent studies have shed light on the critical role of the extracellular matrix (ECM) in IPF development, where the ECM communicates with cells and initiates a positive feedback loop to promote fibrotic processes. Stemming from this shift in the understanding of fibrosis, there is a need to develop in vitro model systems that mimic the human lung microenvironment to better understand how biochemical and biomechanical cues drive fibrotic processes in IPF. However, current in vitro cell culture platforms, which may include substrates with different stiffness or natural hydrogels, have shortcomings in recapitulating the complexity of fibrosis. This review aims to draw a roadmap for developing advanced in vitro pulmonary fibrosis models, which can be leveraged to understand better different mechanisms involved in IPF and develop drug candidates with improved efficacy. We begin with a brief overview defining pulmonary fibrosis and highlight the importance of ECM components in the disease progression. We focus on fibroblasts and myofibroblasts in the context of ECM biology and fibrotic processes, as most conventional advanced in vitro models of pulmonary fibrosis use these cell types. We transition to discussing the parameters of the 3D microenvironment that are relevant in pulmonary fibrosis progression. Finally, the review ends by summarizing the state of the art in the field and future directions.
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How this classification was reachedexpand
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) | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".