Emerging drugs for the treatment of L-DOPA-induced dyskinesia: an update
Bibliographic record
Abstract
INTRODUCTION: Prolonged treatment with L-3,4-dihydroxyphenylalanine (L-DOPA) leads to the development of uncontrolled movements (L-DOPA-induced dyskinesias (LID)) in Parkinson's disease (PD). There is currently only a single approved drug for the treatment of LID, a long-acting preparation of the NMDA antagonist, amantadine, that has variable benefits and side-effects. Therefore, new treatments for LID remain an unmet in PD. AREAS COVERED: We review the current strategies for the management of LID; the pathogenic mechanisms underlying the development of LID, which provides the rationale for clinical trials of novel targets for LID and provide a review of phase II/III trials for emerging drugs for LID, with either positive results, or ongoing studies, reported between January 2014 and December 2019. EXPERT OPINION: There are several ongoing studies for agents that showed possible benefit at phase Ib/IIa for reducing LID. However, there are no new positive phase III double-blind randomized controlled clinical trials (DBRCT) for emerging treatments for LID. Generating better preclinical models, more precise recruitment tools and better outcome measures remain a priority. The pharmacology of drugs investigated for LID may be too selective; therefore, evaluating combinations of drugs is worthy of consideration as is the repurposing of existing drugs with multiple pharmacological targets.
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 | 0.001 | 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) | 0.009 | 0.004 |
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".