ASP2409, A Next-Generation CTLA4-Ig, Versus Belatacept in Renal Allograft Survival in Cynomolgus Monkeys
Bibliographic record
Abstract
Belatacept is the first costimulatory blockade agent approved for maintenance immunosuppression in kidney transplant recipients. Clinical results have indicated that belatacept is associated with superior renal function and improved metabolic profile; however, higher incidence of acute rejection and posttransplant lymphoproliferative disorder are the shortcomings of this agent. In this study, ASP2409, a new cytotoxic T-lymphocyte associated protein 4-immunoglobulin possessing 14-fold higher in vitro CD86 binding affinity than belatacept, was tested for renal allograft survival in cynomolgus monkeys. ASP2409 monotherapy dose-dependently prolonged renal allograft survival. Low-dose ASP2409 in combination with a subtherapeutic dose of tacrolimus showed much longer median survival time than monotherapy. Similar allograft survival results were observed in regimens based on high-dose ASP2409, belatacept, and therapeutic-dose tacrolimus. The results of renal allograft histopathology with high-dose ASP2409-based regimens were not inferior to the belatacept-based regimen. Moreover, higher frequencies of FoxP3-positive regulatory T cells in renal allografts were observed in ASP2409- and belatacept-based regimens compared with tacrolimus-based regimens. No serious side effects related to ASP2409 administration were found during the study. These data suggest that ASP2409 is a promising candidate for calcineurin inhibitor-sparing or -avoidance regimens.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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 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".