In Vitro and In Vivo Comparison of Random versus Site-Specific Conjugation of Bifunctional Chelating Agents to the CD33-Binding Antibody for Use in Alpha- and Beta-Radioimmunotherapy
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Radiometal chelator conjugation is a cornerstone of radioimmunotherapy (RIT). Continued interest in selective placement of chelators remains an active topic of discussion in the field. With several simple site-specific methods being recently reported, it was of interest to investigate the benefits and potential drawbacks of the site-specific method with a full comparison to a more typical random conjugation method that is currently utilized in clinical applications. In this study, the conjugation methods were evaluated side by side to determine the utility of both methods using commercially available random and site-specific conjugation reagents by performing antigen binding; radiolabeling with 64 Cu, 177 Lu, and 225 Ac radioisotopes; antibody-conjugate stability, cytotoxicity, in vivo distribution, pharmacokinetics analyses, and dosimetry to gather a whole data set for preclinical investigation. Evaluation revealed that both methods performed similarly during most experiments with the site-specific method, resulting in higher binding capacity of the antibody conjugate via flow cytometry. Radiolabeling was not significantly different between two methods, while stability showed that the site-specifically conjugated antibody was somewhat more stable at 37 °C in human serum over 1 week. In vitro experiments demonstrated less cell killing with the random conjugation method, while in vivo experiments showed no statistical differences in tumor uptake between conjugation methods. Dosimetry calculations were performed using the acquired PET/CT data and showed that apart from the liver, there was no significant difference in radiation doses delivered by either antibody conjugate. These results demonstrate that both methods are viable for future work, while the site-specific method offers several potential advantages and, in some cases, improved efficacy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".