Radiolabeling and Preliminary In Vivo Evaluation of the Candidate CCR2 Targeting PET Radioligand [11C]AZD2423
Bibliographic record
Abstract
Background: AZD2423 is a high-affinity and selective negative allosteric modulator of the chemokine receptor type 2 (CCR2). This receptor plays important roles in the extravasation and transmigration of monocytes under inflammatory conditions. The aims of the current positron emission tomography (PET) study were as follows: (i) to develop an efficient synthetic method for labeling AZD2423 with carbon-11 (11C, t1/2 = 20.4 min) and (ii) to evaluate its potential to visualize CCR2 binding in the non-human primate (NHP) brain. Methods: [11C]AZD2423 was synthesized using a novel two-step, two-pot [11C]carbon monoxide carbonylation procedure. PET imaging studies in NHPs (n = 2) were conducted to assess its brain penetration and in vivo distribution. Results: Radiolabeling of [11C]AZD2423 was accomplished with good yield (7.4 ± 0.6%, n = 4) and high radiochemical purity (>99%) using [11C]carbon monoxide. Preliminary PET imaging in NHPs revealed low [11C]AZD2423 brain exposure under both baseline and pretreatment conditions (SUVpeak = 0.4, n = 2). However, high concentrations of radioactivity were observed in organs outside the brain at baseline, e.g., the thyroid gland (SUVpeak = 3.3, n = 2), parotid gland (SUVpeak = 3.4, n = 2), and submandibular gland (SUVpeak = 4.4, n = 2). This radioactivity was markedly reduced following pretreatment with AZD2423 (3.0 mg/kg), indicating specific binding of [11C]AZD2423 to CCR2 in vivo. The presence of specific CCR2 binding was further validated using two-tissue compartment modeling, which demonstrated a 59–63% reduction in the total volume of distribution values in the analyzed peripheral tissues. Conclusions: Altogether, [11C]AZD2423 shows potential as a PET radioligand for the in vivo visualization of CCR2 expression in tissues outside the brain and may also serve as a lead compound for the further development of a CCR2 PET radioligand suitable for brain imaging.
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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 | 0.001 | 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".