Novel and emerging drugs for the treatment of Crohn’s disease: a review of phase II and III trials
Bibliographic record
Abstract
INTRODUCTION: Crohn's disease (CD) is a chronic inflammatory bowel disease characterized by unpredictable flare-ups and periods of remission. While several therapeutic options, such as anti-tumor necrosis factor (TNF), anti-integrin, and interleukin (IL) 12/23 inhibitors, as well as IL-23 and Janus kinase (JAK) inhibitors, have been approved for CD treatment, a substantial number of patients fail to respond adequately or experience a loss of response over time. In recent years, the scientific community has been actively investigating novel agents to address these challenges and improve the management of CD. AREAS COVERED: This comprehensive narrative review provides an overview of recent developments in CD treatment, summarizing phase 2 and phase 3 clinical trial data. We delve into the clinical efficacy and safety profiles of emerging therapies, encompassing JAK inhibitors, IL-23 inhibitors, anti-adhesion molecules, S1P1 receptor modulators, and combined targeted treatments. EXPERT OPINION: The armamentarium of CD therapeutic agents is constantly expanding. We analyze pivotal findings from phase 2 and phase 3 CD treatment trials. We also underscore the existing gaps in therapy and the paramount role of ongoing research and innovation in CD management.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".