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Benefit Ledger · provisional · Medicine & Health

Immorta Bio says AI helped identify SenoMune-0257, a nine-amino-acid senolytic peptide

On 12 October 2026 Immorta Bio announced it had finished planned preclinical studies of SenoMune-0257, a synthetic nine-amino-acid peptide it says AI helped select to stimulate T cells against senescent cells. The company aims for first human evaluation before year-end 2026. No sequence, named model, public data package, or trial site was disclosed.

Tier 1 UsefulMethodology 0.2
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Current score

+0.02

1 base · Useful (tier 1 of 5, 1 pts)
× 0.4000 attribution · Material acceleration
× 0.3000 evidence · Technical disclosure or preprint
× 0.4000 realization · Demonstrated
× 0.4000 durability · Temporary or quickly replaceable
Event-level product before credit split: 0.02

Unpublished in-vitro clearance of senescent cells, if true, is Useful (tier 1), not Notable. Peer-reviewed mouse leads such as abaucin sit higher; Phase 2a is the clinical Notable floor. AI helped propose peptide candidates that humans then filtered in the lab, on top of prior SenoVax biology (0.40). Evidence is a company announcement plus trade coverage, not a preprint (0.20). Realization is a claimed laboratory demonstration, not independent experimental validation or a trial (0.40). Durability is limited until the candidate is published or fails (0.40). The model stays unspecified. Score: 1 × 0.40 × 0.20 × 0.40 × 0.40 × 1.00 = 0.0128. Follow-up ingest: independent source raised evidence; added a follow-up source.

What happened

Longevity.technology reported the claim on 23 October 2026 from Immorta Bio’s 12 October PR Newswire release. The Miami company says SenoMune-0257 is a short synthetic peptide designed to restore immune surveillance of senescent cells rather than kill them with a small-molecule senolytic. President and CSO Thomas Ichim said AI identified dozens of peptide candidates that were then narrowed by computation and laboratory work. Company laboratory studies are said to have stimulated cytotoxic T cells that selectively eliminated senescent cells while sparing healthy cells “under the conditions tested.” The peptide is described as a simpler, off-the-shelf follow-on to SenoVax, Immorta’s earlier senescent-cell immunization work published in the Journal of Translational Medicine. Landmark mouse senolytic papers cited in the release (Baker 2016; Xu 2018) are field context, not results for this molecule. The announcement does not publish the sequence, assay details, animal data, a named model or design tool, a preprint, or an IND/trial location. Human safety and efficacy are explicitly unestablished. First-in-human evaluation is a plan, not a started trial. This ledger records a company-reported preclinical candidate nomination, not a demonstrated aging therapy. Update (2026-10-26): Mathematical AI Predicts 40% and 57% Influenza Vaccine Effectiveness Against H1N1 and H3N2, Respectively, for the 2026--2027 U.S. Season . Background: Clinical influenza vaccine effectiveness (VE) has often been low over the past two decades, highlighting the need for preseason VE forecasting. Timely forecasts could help health authorities plan prevention strategies and allocate healthcare resources. However, preseason forecasting of clinical influenza VE remains relatively uncommon. Methods: We obtained hemagglutinin (HA) sequences from GISAID for U.S. specimens collected in August--September before each influenza season from 2010--2011 through 2024--2025. After quality screening, we compared each virus with the corresponding vaccine target strain for the same season and subtype or lineage using two mathematical distances based on amino acid patterns in the HA protein. We calculated mean distances for each season and subtype or lineage and paired them with published clinical VE estimates, yielding 26 observations across 13 seasons. Using a mathematical AI approach, we fitted linear regression models of VE against each distance and evaluated their predict

Model attribution

Unspecified AI system
Version unspecified
+0.02

Unspecified

Unnamed computational tools Immorta says identified dozens of peptide candidates later narrowed to SenoMune-0257.

Ichim attributes candidate identification to artificial intelligence plus computational filtering and laboratory experimentation. No vendor, model family, or named release is identified. Prior SenoVax immunology is human work.

Attribution 0.4000 · Credit share 100% · Unknown

Claims

  • Immorta Bio announced completion of planned preclinical studies for SenoMune-0257, a nine-amino-acid peptide it says AI helped identify to stimulate T cells against senescent cells.

    outcome · supported

  • In company laboratory studies, the peptide stimulated cytotoxic T cells that selectively eliminated senescent cells while sparing healthy cells under the conditions tested.

    outcome · supported

  • SenoMune-0257 is a demonstrated human therapy that clears senescent cells, extends lifespan, or treats age-related disease.

    significance · disputed

  • A named model or vendor designed the peptide.

    attribution · disputed

Sources

primary sources

independent sources

Secondary domains: Biology, Chemistry

Revision history

  • 24 Oct 2026 · 0.00 → 0.01

    Imported events under methodology 0.2.

  • 26 Oct 2026 · 0.01 → 0.02

    Ingest update: independent source raised evidence; added a follow-up source.

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