From Preclinical to Clinical Trials: An Update on Potential Therapies for Huntington’s Disease
Bibliographic record
Abstract
Huntington’s disease (HD) is a neurodegenerative disorder caused by a CAG expansion in the HD gene that codifies the protein huntingtin and characterized by neurodegeneration of certain areas of the brain, particularly the striatum and the cortex. The first symptoms usually appear in mid-life and include cognitive deficits and motor disturbances that progress over time. The disease is invariable fatal and there is currently no cure for individuals affected with this disorder. In a search to find a cure for this devastating neurodegenerative disorder, numerous pharmacological compounds have now been tested through preclinical trials that have heavily relied on the various transgenic mouse models that are currently available to study HD. Unfortunately however, to date the benefits observed in the clinical setting have been somewhat limited. We have recently published a review article comparing the results of these preclinical studies with the outcomes of the corresponding clinical trials involving HD afflicted individuals (Brocardo and Gil- Mohapel, 2012, Current Psychopharmacology 1:137-154). In the present article we present an update to our previous review, where the new preclinical and clinical studies that have been performed over the past year have been also discussed with the goal of further elucidating the efficacy of the pharmacological treatments that have been attempted in both transgenic HD mouse models and human HD patients. By providing and maintaining an up-to-date overview of the most current literature, we hope that patterns will emerge that will guide the design of more effective preclinical and clinical studies, such as the use of combination therapies that utilize different cocktails of pharmacological compounds to simultaneously target different intracellular pathways that are affected in HD. Keywords: Behavioural deficits, clinical trial, Huntington’s disease, neuropathology, preclinical study, transgenic model, therapeutic strategy.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.006 |
| 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".