Safety, pharmacokinetics, and pharmacodynamics of MK-6194, an IL-2 mutein designed to selectively activate regulatory T cells: single ascending dose and multiple ascending dose trial data
Bibliographic record
Abstract
MK-6194, an interleukin-2 mutein designed to selectively activate regulatory T cells (Tregs), was evaluated for safety, pharmacokinetics (PK), immunogenicity, and pharmacodynamics in healthy participants. In a single ascending dose trial (N = 56), participants received subcutaneous MK-6194 or placebo (3:1 ratio) across dose levels ranging from 1 to 10 mg. In a multiple ascending dose trial (N = 54), participants received subcutaneous MK-6194 or placebo (3:1 ratio) at dose levels ranging from 0.5 to 5 mg every 2 wk (total 3 doses) as well as 5 mg every 4 wk (total 2 doses). Baseline characteristics were comparable between trials, with participants mostly male with a mean age of 36 yr. There were no serious adverse events or dose-limiting toxicities. The most common adverse events were injection site erythema and eosinophil count elevations (with no indication of severe eosinophilia or eosinophilia-related organ damage). PK showed dose-proportionality and repeated doses of MK-6194 did not result in accumulation or time-dependent PK. Immunogenicity was low with no impact on PK or safety. Treg expansion as assessed by flow cytometry and Treg-specific demethylation region analysis was observed in a dose-dependent manner during both trials and expanded within about 8 d postdose up to about 5-fold and returned to baseline by 14 to 29 d postdose. Minimal impact was observed on other lymphocytes including total T lymphocyte and natural killer cell counts. These findings support the further development of MK-6194 as a potential treatment for autoimmune disorders.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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) | 0.002 | 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".