Biologics in the Management of Chronic Obstructive Pulmonary Disease: Emerging Perspectives
Bibliographic record
Abstract
Inflammation is at the core of multiple, highly variable, and interconnected pathological processes, which will eventually sow the seeds of chronic bronchitis and/or emphysema in exposed and susceptible individuals. Low-grade chronic inflammation in these patients is acutely worsened during infectious, and to a lower extent, non‑infectious COPD exacerbations. Unfortunately, a large fraction of patients receiving contemporary anti-exacerbation prophylaxis–including that provided by inhaled combinations of long-acting β2-adrenoceptor agonist (LABA), long-acting anti‑muscarinic (LAMA), and inhaled corticosteroids (ICS) (triple therapy)–remain frequent exacerbators. These patients have at least two moderate episodes and/or one severe episode requiring hospitalization or an emergency department visit in the preceding year. Given their higher risk of disease progression and premature death, recent national and international guidelines for pharmacological COPD treatment consider them as “high-risk” patients. The hope of providing more effective protection against exacerbations through anti‑inflammatory, non-steroidal alternatives has sparked major research efforts in the past few years. This focused review will concisely highlight the pharmacological approaches based on anti-inflammatory biologics currently under investigation, emphasizing the few options more likely to be available in the Canadian market in 2025–2026. Two recent meta-analyses provide valuable information for those interested in further methodological details of the studies herein cited.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".