Poster - Thur Eve - 15: Production and assessment of astatine-211 for targeted alpha therapy
Bibliographic record
Abstract
Biologically-targeted alpha-particle radiation is the basis of new and promising treatments for eliminating disseminated micrometastases and the residual microscopic malignancies that remain after surgery or radiation therapy. The short-range alpha-particles are highly cytotoxic and capable of inactivating single, isolated cancer cells which may otherwise cause recurrence. Astatine-211 is a promising alpha emitter for therapy; the 7.2 hour half-life of 211At provides sufficient time for biological-targeting to take place. However, this radionuclide is in short supply and future treatment strategies still require extensive preclinical evaluation. The present work aims to develop technologies that (1) increase the world-wide availability of 211At for clinical use, and (2) assess the risks of 211At-based therapies by quantifying the activity distributions in animal models. At TRIUMF (Vancouver, BC), the feasibility of a novel generator system for 211At is under investigation which would allow distribution of 211At across Canada and internationally. Briefly, a longer-lived parent radionuclide of 211At, radon-211, would be produced and allowed to decay in containment to yield 211At in solution. Additionally, a supplementary study is underway in collaboration with the University of Washington to evaluate the sub-organ biodistributions of astatinated targeting biomolecules, with cell-level resolution. These measurements involve high resolution quantitative alpha-particle imaging in thin tissue samples and can be done for a selection of applications (eg. lymphoma, metastatic prostate cancer, etc) using animal models. The planned alpha-camera measurements are primarily designed to predict and assess the risk of toxicity associated with 211At-based therapies and aid in developing the future clinical applications.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".