From Inhibitors to PET: SAR-Based Development of [<sup>18</sup>F]SK60 for mIDH1 Imaging
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Mutations in isocitrate dehydrogenase 1/2 (mIDH1/2) are clinically significant biomarkers for diagnosis, prognosis, and therapy in cancer. To advance the noninvasive molecular imaging of mIDH1, we aim to develop a positron emission tomography (PET) radiotracer targeting IDH1R132H, the most common type of mIDH1/2. Starting from compound GSK321, a systematic structure–activity relationships (SAR) optimization was performed leading to the dimethylated derivative SK60 ( 19 ) with low nanomolar potency and high selectivity for IDH1R132H. Consequently, [ 18 F]SK60 was developed via copper-mediated radiofluorination. Various in vitro studies with [ 18 F]SK60 showed a high fraction of nonspecific binding. The in vivo evaluation revealed high metabolic stability with no detectable brain-permeable radiometabolite. In addition, limited brain uptake was observed by PET suggesting that further structural modifications to reduce lipophilicity might be needed for this structure. The present study led thus to a novel series of dimethylated GSK321 derivatives for further investigation in IDH1R132H-related therapies and PET imaging.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".