Bibliographic record
Abstract
INTRODUCTION: Neuropathic pain is a costly and disabling condition, which affects up to 8% of the population. Available therapies often provide incomplete pain relief and treatment-related side effects are common. Preclinical neuropathic pain models have facilitated identification of several promising targets, which have progressed to human clinical phases of evaluation. AREAS COVERED: A systematic database search yielded 25 new molecular entities with specified pharmacological mechanisms that have reached Phase II or III clinical trials. These include calcium channel antagonists, vanilloid receptor antagonists, potassium channel agonists, NMDA antagonists, novel opioid receptor agonists, histamine H3 receptor antagonists, a novel sodium channel antagonist, serotonin modulators, a novel acetylcholine receptor agonist, α-2b adrenoreceptor agonist, cannabinoid CB2 receptor agonist, nitric oxide synthase inhibitor, orexin receptor antagonist, angiotensin II 2 antagonist, imidazoline I2 receptor agonist, apoptosis inhibitor and fatty acid amide hydrolase inhibitor. EXPERT OPINION: Although the diversity of pharmacological mechanisms of interest emphasise the complexity of neuropathic pain transmission, the considerable number of agents under development reflect a continued enthusiasm in drug development for neuropathic pain. Ongoing enhancements in methodology of both preclinical and clinical research and closer translation in both directions are expected to more efficiently identify new agents, which will improve the management of neuropathic pain.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.014 | 0.006 |
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".