t-Bu2SiF-Derivatized D2-Receptor Ligands: The First SiFA-Containing Small Molecule Radiotracers for Target-Specific PET-Imaging
Bibliographic record
Abstract
The synthesis, radiolabeling and in vitro evaluation of new silicon-fluoride acceptor (SiFA) derivatized D(2)-receptor ligands is reported. The SiFA-technology simplifies the introduction of fluorine-18 into target specific biomolecules for Positron-Emission-Tomography (PET). However, one of the remaining challenges, especially for small molecules such as receptor-ligands, is the bulkiness of the SiFA-moiety. We therefore synthesized four Fallypride SiFA-conjugates derivatized either directly at the benzoic acid ring system (SiFA-DMFP, SiFA-FP, SiFA-DDMFP) or at the butyl-side chain (SiFA-M-FP) and tested their receptor affinities. We found D(2)-receptor affinities for all compounds in the nanomolar range (K(i(SiFA-DMFP)) = 13.6 nM, K(i(SiFA-FP)) = 33.0 nM, K(i(SiFA-DDMFP)) = 62.7 nM and K(i(SiFA-M-FP)) = 4.21 nM). The radiofluorination showed highest yields when 10 nmol of the precursors were reacted with [(18)F]fluoride/TBAHCO(3) in acetonitrile. After a reversed phased cartridge purification the desired products could be isolated as an injectable solution after only 10 min synthesis time with radiochemical yields (RCY) of more than 40% in the case of SiFA-DMFP resulting in specific activities >41 GBq/µmol (>1,100 Ci/mmol). Furthermore, the radiolabeled products were shown to be stable in the injectable solutions, as well as in human plasma, for at least 90 min.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".