Dose‐dependent inactivation of airway tryptase with a novel dissociating anti‐tryptase antibody (MTPS9579A) in healthy participants: A randomized trial
Bibliographic record
Abstract
Abstract Tryptase is the most abundant secretory granule protein in human lung mast cells and plays an important role in asthma pathogenesis. MTPS9579A is a novel monoclonal antibody that selectively inhibits tryptase activity by dissociating active tetramers into inactive monomers. The safety, tolerability, pharmacokinetics (PKs), and systemic and airway pharmacodynamics (PDs) of MTPS9579A were assessed in healthy participants. In this phase I single‐center, randomized, observer‐blinded, and placebo‐controlled study, single and multiple ascending doses of MTPS9579A were administered subcutaneously (s.c.) or intravenously (i.v.) in healthy participants. In addition to monitoring safety and tolerability, the concentrations of MTPS9579A, total tryptase, and active tryptase were quantified. This study included 106 healthy participants (82 on active treatment). Overall, MTPS9579A was well‐tolerated with no serious or severe adverse events. Serum MTPS9579A showed a dose‐proportional increase in maximum serum concentration (Cmax) values at high doses, and a nonlinear increase in area under the curve (AUC) values at low concentrations consistent with target‐mediated clearance were observed. Rapid and dose‐dependent reduction in nasosorption active tryptase was observed postdose, confirming activity and the PK/PD relationship of MTPS9579A in the airway. A novel biomarker assay was used to demonstrate for the first time that an investigative antibody therapeutic (MTPS9579A) can inhibit tryptase activity in the upper airway. A favorable safety and tolerability profile supports further assessment of MTPS9579A in asthma. Understanding the exposure‐response relationships using the novel PD biomarker will help inform clinical development, such as dose selection or defining patient subgroups.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".