Advances in [18F]Trifluoromethylation Chemistry for PET Imaging
Bibliographic record
Abstract
Positron emission tomography (PET) is a preclinical and clinical imaging technique extensively used to study and visualize biological and physiological processes in vivo. Fluorine-18 (18F) is the most frequently used positron emitter for PET imaging due to its convenient 109.8 min half-life, high yield production on small biomedical cyclotrons, and well-established radiofluorination chemistry. The presence of fluorine atoms in many drugs opens new possibilities for developing radioligands labelled with fluorine-18. The trifluoromethyl group (CF3) represents a versatile structural motif in medicinal and pharmaceutical chemistry to design and synthesize drug molecules with favourable pharmacological properties. This fact also makes CF3 groups an exciting synthesis target from a PET tracer discovery perspective. Early attempts to synthesize [18F]CF3-containing radiotracers were mainly hampered by low radiochemical yields and additional challenges such as low radiochemical purity and molar activity. However, recent innovations in [18F]trifluoromethylation chemistry have significantly expanded the chemical toolbox to synthesize fluorine-18-labelled radiotracers. This review presents the development of significant [18F]trifluoromethylation chemistry strategies to apply [18F]CF3-containing radiotracers in preclinical and clinical PET imaging studies. The continuous growth of PET as a crucial functional imaging technique in biomedical and clinical research and the increasing number of CF3-containing drugs will be the primary drivers for developing novel [18F]trifluoromethylation chemistry strategies in the future.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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 teacher head, 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".