Disease Targeting Properties of Voclosporin in Kidney Transplant and Lupus Nephritis Patients
Bibliographic record
Abstract
Background: Voclosporin (VCS), a second generation calcineurin inhibitor, is approved in the United States and Europe for the treatment lupus nephritis (LN) in combination with background immunosuppressive therapy. VCS does not require therapeutic drug monitoring, and is associated with improved glucose, lipid and electrolyte profiles compared to tacrolimus and cyclosporine. VCS demonstrates non-linear selective tissue disposition in animal models, and in renal transplant and LN clinical trials. Pharmacometric modeling was conducted to assess the selective tissue drug disposition relative to systemic drug exposure in patients with renal transplant or LN, comparing with healthy volunteers. Methods: Individual VCS blood concentration-time measurements were pooled from single and multiple dose ascending studies in healthy volunteers, the Phase IIb PROMISE study in renal transplant patients, and the Phase II AURA-LV and Phase III AURORA 1 studies in LN patients. The VCS blood exposure data were pharmacometrically modelled using a two-compartment model. Results: In healthy subjects, VCS has comparable central and peripheral volume of distribution (Vc/Vp of 242/272 L/L) and higher elimination than distribution clearance (CL/Q of 43/16 [L/hr]/[L/h]). In transplant patients, VCS has larger peripheral than central volume of distribution (Vc/Vp of 62/2140 L/L), comparable elimination versus distribution clearance (CL/Q of 58/54 [L/hr]/[L/h]) In LN patients, VCS also has larger peripheral than central volume of distribution (Vc/Vp of 34/2120 L/L), slower distribution than elimination clearance (CL/Q of 41/6 [L/hr]/[L/h]). Conclusion: The larger peripheral volume of distribution indicates selective peripheral tissue uptake of VCS in patients with renal transplant and LN. This is consistent with immunosuppressive activity of VCS in targeted organs relative to blood circulation. The low blood levels of VCS are consistent with the safety profile of VCS compared to other calcineurin inhibitors. Overall, the higher concentration of VCS in affected tissues may account for the efficacy and safety profiles reported in renal transplant and LN patients. Funding: Commercial Support - Aurinia Pharmaceuticals Inc.
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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 | 0.001 |
| 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 | 0.001 | 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 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".