Development and application of a thin‐film molecularly imprinted polymer for the measurement of mycophenolic acid in human plasma
Bibliographic record
Abstract
Abstract Background Mycophenolic acid (MPA) is used to suppress the immune response following organ transplantation; however, complex pharmacokinetic behavior and a large interpersonal variability necessitate therapeutic drug monitoring. To overcome the limitations of current sample preparation techniques, we present a novel thin‐film molecularly imprinted polymer (TF‐MIP) extraction device as part of a simple, sensitive, and fast method for analysis of MPA from human plasma. Methods Mycophenolic acid is extracted from plasma using a tailor‐made TF‐MIP that is subsequently desorbed into an organic solvent system compatible with mass spectrometry. The MIP yielded higher recovery of MPA relative to a corresponding non‐imprinted polymer. The method allows for the determination of MPA in 45 min including analysis time and can be scaled for high throughput to process as many as 96 samples per hour. Results The method gave an LOD of 0.3 ng mL−1 and was linear from 5 to 250 ng mL−1. Patient plasma samples (35 μL) were diluted using charcoal‐stripped pooled plasma to a final extraction volume of 700 μL; when MPA in patient plasma is high, this ratio can easily be adjusted to ensure samples are within the method linear range. Intra‐ and inter‐day variability were 13.8% and 4.3% (at 15 ng mL−1) and 13.5% and 11.0% (at 85 ng mL−1), respectively (n = 3); inter‐device variability was 9.6% (n = 10). Conclusions Low inter‐device variability makes these devices suitable for single use in a clinical setting, and the fast and robust method is suitable for therapeutic drug monitoring, where throughput and time‐to‐result are critical.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".