Continuous-flow synthesis of [<sup>11</sup>C]raclopride, a positron emission tomography radiotracer, on a microfluidic chip
Bibliographic record
Abstract
11C-labelled radiotracers such as [11C]raclopride are produced in a process that can take between 45 and 60 min to complete. These conventional approaches can consume upwards of 75% of the 11C (t1/2 = 20 min) due to radioactive decay alone, even more if synthesis losses are considered. To compensate, a large starting quantity of radioactive precursors such as [11C]methyl iodide is required to produce an adequate amount of the tracer for injection. In this investigation, a continuous-flow microchip is explored for the purpose of synthesizing 11C radiotracers in a shorter time by exploiting the favorable reaction kinetics of using smaller reaction volumes. To enhance the mixing of reagents within the microchannel, a micromixer “loop” design was used in fabricating various polydimethylsiloxane chip styles. With a loop design implemented in an abacus-style chip for the production of nonradioactive raclopride, shorter reaction times, reduced precursor use, and improved yields were possible when compared with the use of a simple serpentine design (no loop-style chip). However, when performing the equivalent radiochemical reaction, the results were not as favorable. Using the loop design in a full loop-style chip, parameters such as premixing the reagents, reducing flow rate, and varying reagent concentrations were explored to improve the yields of [11C]raclopride (in terms of relative radioactivity) formed. The full loop chip design produced the best results, and future work will see the polydimethylsiloxane prototype chip design translated into a glass chip for further optimization.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".