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1036 KAN-004, a metabolically complete live biotherapeutic product for the treatment of immune-related colitis

2025· article· W4415899279 on OpenAlexaff
James E. Berleman, Lee R. Swem, Kyle Jacoby, Peter J Diebold, K. Robertson, Aditya Bhalla, Jackson Mintz, Pallavi Murugkar, Hannah Bronson, Meriem Messaoudene, Anna Pérez, Wiam Belkaïd, Marguerite Prior, Philip Burnham, Hao Shi, Mark Weinberg, Bertrand Routy, Arielle Elkrief, Matthew P. Cheng

Bibliographic record

VenueRegular and Young Investigator Award Abstracts · 2025
Typearticle
Language
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsUniversité de MontréalCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsProduct (mathematics)ColitisUlcerative colitisInflammatory bowel diseaseInflammation

Abstract

fetched live from OpenAlex

Background Immune checkpoint inhibitors (ICI) have transformed cancer therapy but are frequently complicated by immune-related adverse events (irAEs), particularly immune-related diarrhea or colitis (irColitis), which can necessitate immunosuppression and ICI discontinuation. Fecal microbiota transplantation (FMT) has shown promise in treating irColitis, but concerns around donor variability, infection risk, and scalability limit the utility and scalability of FMT. KAN-004 is a defined live biotherapeutic product (LBP) composed of >100 commensal strains, rationally selected from FMT-qualified healthy human donors to restore gut microbial composition, metabolic function, and microbiome-immune balance in patients with irColitis.Methods Preclinical studies evaluated the impact of KAN-004 in two murine models of antibiotics-induced dysbiosis, and an acute dextran sodium sulfate (DSS)-induced colitis model. Further, the impact of KAN-004 as a co-treatment concurrent with anti-PD-1 therapy was investigated in two tumor models (MCA-205 in germ-free mice and E0771 in SPF mice). Endpoints included microbial engraftment, metabolite recovery, histopathologic scoring, clinical colitis indices, tumor response and flow cytometry.Results In murine models oral supplementation of KAN-004 achieved rapid, durable engraftment with strain detection by day 2 and sustained levels through day 60. While targeted Short Chain Fatty Acids (SCFAs) were undetectable at baseline following antibiotic pre-treatment, KAN-004 restored a naïve-like SCFA profile by day 9, unlike the delayed and imbalanced recovery seen with vehicle. In an DSS colitis model, KAN-004 significantly improved survival (80% vs. 10%, p = 0.0027), reduced clinical severity (p = 0.002), and preserved epithelial barrier integrity. When combined with anti-PD-1 therapy in an MCA-205 tumor model, KAN-004 enhanced anti-PD-1 efficacy compared to FMT from ICI responder donors (p = 0.008). In an E0771 ICI resistant tumor model, combination anti-PD-1 and KAN-004 treatment showed a trend for decrease in tumor size compared to isotype control (p = 0.055), with increased tumor infiltration of CD8+ effector T cells compared to FMT from ICI responder donors (p = 0.02).Conclusions KAN-004 demonstrates preclinical efficacy in resolving irColitis and enhancing antitumor immunity in various models. Novel method developments by Kanvas Biosciences provide precise strain-level composition for assessing microbial kinetics and GMP manufacturing. In collaboration with the Centre Hospitalier de l’Université de Montréal (CHUM), a phase I clinical trial of KAN-004 in patients with irColitis is planned to begin in Q4 2025.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.002

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.

Opus teacher head0.012
GPT teacher head0.249
Teacher spread0.237 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

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Citations0
Published2025
Admission routes1
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