A new era in idiopathic pulmonary fibrosis: considerations for future clinical trials
Bibliographic record
Abstract
The past decade has seen substantial progress in understanding the pathobiology, natural history, and clinical significance of idiopathic pulmonary fibrosis (IPF), culminating in the establishment of two effective medical therapies. Now seems an important time to reconsider the design and conduct of future IPF clinical trials. Building on lessons learned over the past decade, we use this perspective to lay out four key considerations for moving forward effectively and efficiently with the next generation of clinical trials in IPF. These are: development of a coordinated IPF clinical trials network; establishment of expectations for early phase proof of concept studies; adaptation of late-phase efficacy trial designs to the emergence of approved therapies, and; agreement on primary end-points for late phase clinical trials. Continued progress in the field of IPF will require creativity and collaboration on the part of all stakeholders. We believe that addressing these four considerations will encourage and enable investment in this new era of drug development in IPF, and will lead to more rapid development of effective therapies.
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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 | 0.368 | 0.285 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.016 |
| Scholarly communication | 0.016 | 0.036 |
| Open science | 0.008 | 0.009 |
| Research integrity | 0.037 | 0.038 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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".