Biomarkers of Crohn’s Disease to Support the Development of New Therapeutic Interventions
Bibliographic record
Abstract
BACKGROUND: Currently, 2 coprimary end points are used by health authorities to determine the effectiveness of therapeutic interventions in patients with Crohn's disease (CD): symptomatic remission (patient-reported outcome assessment) and endoscopic remission (ileocolonoscopy). However, there is lack of accepted biomarkers to facilitate regulatory decision-making in the development of novel therapeutics for the treatment of CD. METHODS: With support from the Helmsley Charitable Trust, Critical Path Institute formed the Crohn's Disease Biomarkers preconsortium (CDBpC) with members from the pharmaceutical industry, academia, and nonprofit organizations to evaluate the CD biomarker landscape. Biomarkers were evaluated based on biological relevance, availability of biomarker assays, and clinical validation data. RESULTS: The CDBpC identified the most critical need as pharmacodynamic/response biomarkers to monitor disease activity in response to therapeutic intervention. Fecal calprotectin (FC) and serum C-reactive protein (CRP) were identified as biomarkers ready for the regulatory qualification process. A number of exploratory biomarkers and potential panels of these biomarkers was also identified for additional development. Given the different factors involved in CD and disease progression, a combination of biomarkers, including inflammatory, tissue injury, genetic, and microbiome-associated biomarkers, will likely have the most utility. CONCLUSIONS: The primary focus of the Inflammatory Bowel Disease Regulatory Science Consortium will be development of exploratory biomarkers and the qualification of FC and CRP for IBD. The Inflammatory Bowel Disease Regulatory Science Consortium, focused on tools to support IBD drug development, will operate in the precompetitive space to share data, biological samples for biomarker testing, and assay information for novel biomarkers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.024 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".