Quantitative Characterization of the Smoothness of Extended-release Methylphenidate Pharmacokinetic Profiles.
Bibliographic record
Abstract
Objective: Extended-release methylphenidate (ER-MPH) formulations used to treat attention deficit hyperactivity disorder (ADHD) have complex pharmacokinetic (PK) profiles, resulting from differing ratios of immediate-release and extended-release components and/or their site of absorption. This study aimed to evaluate the smoothness of PK curves of ER-MPHs. Design: The integral of the second derivative squared was evaluated for modeled PK curves, with smaller values indicating a smoother curve. The calculated smoothness of each PK curve was normalized by dividing by Cmax 2 to derive a normalized smoothness parameter appropriate across the dose range of each formulation. Calculations used modeled PK curves from 100mg delayed-release and ER-MPH (DR/ER-MPH), 54mg osmotic release oral system MPH (OROS MPH), 60mg MPH controlled-release delivery (MPH CD), 60mg ER-MPH oral suspension (MEROS), 20mg ER dexmethylphenidate (d-MPH ER), and 60mg multilayer-release MPH (MLR-MPH). Results: The Cmax2-normalized smoothness value was consistent across DR/ER-MPH doses, allowing for relevant comparisons across formulations. Normalized smoothness values differed widely; the lowest normalized smoothness was 0.05 with DR/ER-MPH and ranged up to 9.56 with d-MPH ER. Conclusion: DR/ER-MPH demonstrated a smoother PK profile compared to the highest dose of other ER-MPH formulations. While the benefits of a smooth PK profile remain to be tested clinically, having fewer peaks and troughs has been hypothesized to reduce waxing and waning of therapeutic effects throughout the day, and more gradual changes in MPH plasma levels have been hypothesized to lower the risk of likeability and potentially abate afternoon symptom rebound.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".