Synthesis of [18F]FAZA Using Nosyl and Iodo Precursors for Nucleophilic Radiofluorination
Bibliographic record
Abstract
BACKGROUND: 1-α-D-(5-Deoxy-5-[18F]fluoroarabinofuranosyl)-2-nitroimidazole ([18F]FAZA) is manufactured by nucleophilic radiofluorination of 1-α-D-(2',3'-di-O-acetyl-5'-O-toluenesulfonylarabinofuranosyl)- 2-nitroimidazole (DiAcTosAZA) and alkaline deprotection to afford [18F]FAZA. High yields (>60%) under optimized conditions frequently revert to low yields (<20%) in large scale, automated syntheses. Competing side reactions and concomitant complex reaction mixtures contribute to substantial loss of product during HPLC clean-up. OBJECTIVE: To develop alternative precursors for facile routine clinical manufacture of [18F]FAZA that are compatible with current equipment and automated procedures. METHODS: Two new precursors, 1-α-D-(2',3'-di-O-acetyl-5'-O-(4-nitrobenzene)sulfonyl-arabinofuranosyl)-2- nitroimidazole (DiAcNosAZA) and 1-α-D-(2',3'-di-O-acetyl-5'-iodo-arabinofuranosyl)-2-nitroimidazole (DiAcIAZA), were synthesized from commercially-available 1-α-D-arabinofuranosyl-2-nitroimidazole (AZA). A commercial automated synthesis unit (ASU) was used to condition F-18 for anhydrous radiofluorination, and to radiofluorinate DiAcNosAZA and DiAcIAZA using the local standardized protocol to manufacture [18F]FAZA from AcTosAZA. RESULTS: DiAcNosAZA was synthesized via two pathways, in recovered yields of 29% and 40%, respectively. The nosylation of 1-α-D-(2',3'-di-O-acetyl-arabinofuranosyl)-2-nitroimidazole (DiAcAZA) featured a strong competing reaction that afforded 1-α-D-(2',3'-di-O-acetyl-5'-chloro-arabinofuranosyl)-2- nitroimidazole (DiAcClAZA) in 55% yield. Radiofluorination yields were better from DiAcNosAZA and DiAcIAZA than from DiAcTosAZA, and the presence of fewer side products afforded higher purity [18F]FAZA preparations. Several radioactive and non-radioactive by products of radiofluorination were assigned tentative chemical structures based on co-chromatography with authentic reference compounds. CONCLUSION: DiAcClAZA, a major side-product in the preparation of DiAcNosAZA, and its deprotected analogue (ClAZA), are unproven hypoxic tissue radiosensitizers. DiAcNosAZA and DiAcIAZA provided good radiofluorination yields in comparison to AcTosAZA and could become preferred [18F]FAZA precursors if the cleaner reactions can be exploited to bypass HPLC purification.
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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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".