<sup>212</sup>Pb-Pretargeted Theranostics for Pancreatic Cancer
Bibliographic record
Abstract
Although pancreatic ductal adenocarcinoma (PDAC) is associated with limited treatment options and poor patient outcomes, targeted α-particle therapy (TAT) represents a promising development in the field. TAT shows potential in treating metastatic cancers, including those that have become resistant to conventional treatments. Among the most auspicious radionuclides stands the in vivo α-generator <sup>212</sup>Pb. Combined with the imaging-compatible radionuclide <sup>203</sup>Pb, this theranostic match is a promising modality rapidly translating into the clinic. <b>Methods:</b> Using the pretargeting approach between a radiolabeled 1,2,4,5-tetrazine (Tz) tracer and a <i>trans</i>-cyclooctene (TCO) modified antibody, imaging and therapy with radiolead were performed on a PDAC tumor xenograft mouse model. For therapy, 3 cohorts received a single administration of 1.1, 2.2, or 3.7 MBq of the pretargeting agent, [<sup>212</sup>Pb]Pb-DO3A-PEG<sub>7</sub>-Tz, whereby administered activity levels were guided by dosimetric analysis. <b>Results:</b> The treated mice were holistically evaluated; minimal-to-mild renal tubular necrosis was observed. At the same time, median survival doubled for the highest-dose cohort (10.7 wk) compared with the control cohort (5.1 wk). <b>Conclusion:</b> This foundational study demonstrated the feasibility and safety of pretargeted TAT with <sup>212</sup>Pb in PDAC while considering dose limitations and potential adverse effects.
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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 | 0.000 |
| 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) | 0.001 | 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".