Motor fluctuations in Parkinson disease – a mini-review of emerging drugs
Bibliographic record
Abstract
INTRODUCTION: The symptomatic treatment of Parkinson Disease (PD) relies on levodopa. With disease progression, the response to levodopa becomes variable, leading to fluctuations in benefit on PD symptoms. These motor fluctuations are challenging to manage and negatively impact quality of life in PD. AREAS COVERED: We provide a review of experimental, non-approved pharmacological therapies in phase II and III clinical trials from 2018 to 2024 for PD motor fluctuations. EXPERT OPINION: New formulations of levodopa to improve bioavailability are in development. These include another subcutaneous infusion with efficacy in reducing motor fluctuations and an intranasal delivery with tolerability reported. An oromucosal formulation of apomorphine was safe, further studies are needed. Preliminary results of a phase III study of dopamine D1/D5 agonist tavapadon and phase II of CVN424, a GRP6 inverse agonist suggest improved ON time. Negative studies were reported with foliglurax (MGluR4 inverse agonist) and the repurposed drugs naftazone and bumetanide. Several novel targets are in early-stage development with results awaited. Overall, it is unclear whether the field is significantly further ahead, as the benefit of these emerging drugs in comparison with currently available agents for motor fluctuations needs to be clarified.
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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) | 0.002 | 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) | 0.007 | 0.002 |
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".