Solid Phase <sup>11</sup>C-Methylation, Purification and Formulation for the Production of PET Tracers
Bibliographic record
Abstract
Routine production of radiotracers used in positron emission tomography (PET) mostly relies on wet chemistry where the radioactive synthon reacts with a non-radioactive precursor in solution. This approach necessitates purification of the tracer by high performance liquid chromatography (HPLC) followed by reformulation in a biocompatible solvent for human administration. We recently developed a novel 11C-methylation approach for the highly efficient synthesis of carbon-11 labeled PET radiopharmaceuticals, taking advantage of solid phase cartridges as disposable "3-in-1" units for the synthesis, purification and reformulation of the tracers. This approach obviates the use of preparative HPLC and reduces the losses of the tracer in transfer lines and due to radioactive decay. Furthermore, the cartridge-based technique improves synthesis reliability, simplifies the automation process and facilitates compliance with the Good Manufacturing Practice (GMP) requirements. Here, we demonstrate this technique on the example of production of a PET tracer Pittsburgh compound B ([11C]PiB), a gold standard in vivo imaging agent for amyloid plaques in the human brains.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.008 | 0.012 |
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".