RLS-0071, a dual-targeting anti-inflammatory peptide - biomarker findings from a first in human clinical trial
Bibliographic record
Abstract
Abstract Background RLS-0071 is a novel 15 amino acid peptide dual-targeting anti-inflammatory inhibitor of complement and neutrophil effectors. RLS-0071 inhibits classical complement pathway activation at C1 and blocks the enzymatic activity of myeloperoxidase that leads to the generation of hypochlorous acid and induces NETosis. This peptide is being developed for the treatment of neonatal hypoxic ischemic encephalopathy (HIE) and neutrophilic pulmonary diseases. Methods This was a first in human clinical trial in healthy volunteers to assess safety and pharmacokinetics of single and multiple ascending doses of RLS-0071. Results RLS-0071 single and multiple doses were not associated with any clinically significant changes in safety parameters, laboratory test results or ECG measurements. Adverse events were similar between active drug and placebo groups. The pharmacokinetic profile demonstrated dose proportionality and two-compartment kinetics with rapid tissue distribution. Exploratory biomarker and target engagement assays demonstrated dose dependent classical complement pathway inhibition and myeloperoxidase binding. Discussion/Conclusion RLS-0071 was shown to be safe and well-tolerated at all doses tested with rapid tissue distribution and target engagement for both the classical complement pathway and myeloperoxidase. The findings are supportive of further clinical development and evaluation of RLS-0071 in conditions such as HIE and acute pulmonary diseases. Trial registration ClinicalTrials.gov Identifier: NCT05298787 March 28, 2022. Retrospectively registered.
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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) | 0.001 | 0.001 |
| 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) | 0.011 | 0.002 |
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".