Biodistribution of Yttrium-90–Labeled Anti-CD45 Antibody in a Nonhuman Primate Model
Bibliographic record
Abstract
PURPOSE: Radioimmunotherapy may improve the outcome of hematopoietic cell transplantation for hematologic malignancies by delivering targeted radiation to hematopoietic organs while relatively sparing nontarget organs. We evaluated the organ localization of yttrium-90-labeled anti-CD45 ((90)Y-anti-CD45) antibody in macaques, a model that had previously predicted iodine-131-labeled anti-CD45 ((131)I-anti-CD45) antibody biodistribution in humans. EXPERIMENTAL DESIGN: Twelve Macaca nemestrina primates received anti-CD45 antibody labeled with 1 to 2 mCi of (90)Y followed by serial blood sampling and marrow and lymph node biopsies, and necropsy. The content of (90)Y per gram of tissue was determined by liquid scintillation spectrometry. Time-activity curves were constructed using average isotope concentrations in each tissue at measured time points to yield the fractional residence time and estimate radiation absorbed doses for each organ per unit of administered activity. The biodistribution of (90)Y-anti-CD45 antibody was then compared with that previously obtained with (131)I-anti-CD45 antibody in macaques. RESULTS: The spleen received 2,120, marrow 1,060, and lymph nodes 315 cGy/mCi of (90)Y injected. The liver and lungs were the nontarget organs receiving the highest radiation absorbed doses (440 and 285 cGy/mCi, respectively). Yttrium-90-labeled anti-CD45 antibody delivered 2.5- and 3.7-fold more radiation to marrow than to liver and lungs, respectively. The ratios previously observed with (131)I-anti-CD45 antibody were 2.5-and 2.2-fold more radiation to marrow than to liver and lungs, respectively. CONCLUSIONS: This study shows that (90)Y-anti-CD45 antibody can deliver relatively selective radiation to hematopoietic tissues, with similar ratios of radiation delivered to target versus nontarget organs, as compared with the (131)I immunoconjugate in the same animal model.
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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 | 0.001 | 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".