Novel Molecular Leads for the Prevention of Damage and the Promotion of Repair in Neuroimmunological Disease
Bibliographic record
Abstract
Neuroinflammation is a prominent pathological feature of all neuroimmunological diseases, including, but not limited to, multiple sclerosis (MS), myasthenia gravis, neuromyelitis optica, and Guillain-Barré syndrome. All currently-approved therapies for the treatment of these diseases focus on controlling or modulating the immune (innate and adaptive) responses to limit demyelination and neuronal damage. The primary purpose of this review is to detail the pre-clinical data and proposed mechanism of action of novel drugs currently in clinical trial, with a focus on novel compounds that promote repair and regeneration in the central nervous system (CNS). As the most recent advances have been made in the field of MS research, this review will focus primarily on this disease and its animal models. However, these compounds are likely to be effective for a range of indications with a neuroinflammatory component. Traditionally, MS was thought to proceed through two distinct phases. The first, predominantly inflammatory stage, is characterized by acute episodes of clinical relapse, followed by periods of partial or total recovery with an apparent absence of overall disease progression. In the vast majority of patients, this relapsing-remitting disease subsequently progresses into a second more chronic, neurodegenerative phase, which is characterized by oligodendrocyte damage and axonal destruction leading to brain atrophy and an accumulation of disability. Recent work has shown that rather than occurring independently, both the inflammatory and degenerative phases may run concurrently. This, combined with evidence that early therapeutic intervention slows accumulation of disability and delays progression, highlights the need for novel therapeutic approaches that promote repair and regeneration early in the disease trajectory. Such compounds may be used as monotherapies or in conjunction with classical anti-inflammatory therapies. This review will highlight novel therapies currently in clinical trial, and likely to appear in clinical practice in the near future, focusing on compounds that target the immune system and/or enhance endogenous repair mechanisms in the CNS.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".