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Van Rampelbergh, J.* ; Achenbach, P. ; Leslie, R.D.* ; Kindermans, M.* ; Parmentier, F.* ; Carlier, V.* ; Bovy, N.* ; Vanderelst, L.* ; Van Mechelen, M.* ; Vandepapeliere, P.* ; Boitard, C.*

First-in-human, double-blind, randomized phase 1b study of peptide immunotherapy IMCY-0098 in new-onset type 1 diabetes: an exploratory analysis of immune biomarkers.

BMC Med. 22:259 (2024)
Verlagsversion DOI PMC
Open Access Gold
Creative Commons Lizenzvertrag
Background: IMCY-0098, a synthetic peptide developed to halt disease progression via elimination of key immune cells in the autoimmune cascade, has shown a promising safety profile for the treatment of type 1 diabetes (T1D) in a recent phase 1b trial. This exploratory analysis of data from that trial aimed to identify the patient biomarkers at baseline associated with a positive response to treatment and examined the associations between immune response parameters and clinical efficacy endpoints (as surrogates for mechanism of action endpoints) using an artificial intelligence-based approach of unsupervised explainable machine learning. Methods: We conducted an exploratory analysis of data from a phase 1b, dose-escalation, randomized, placebo-controlled study of IMCY-0098 in patients with recent-onset T1D. Here, a panel of markers of T cell activation, memory T cells, and effector T cell response were analyzed via descriptive statistics. Artificial intelligence-based analyses of associations between all variables, including immune responses and clinical responses, were performed using the Knowledge Extraction and Management (KEM®) v 3.6.2 analytical platform. Results: The relationship between all available patient data was investigated using unsupervised machine learning implemented in the KEM® environment. Of 15 associations found for the dose C group (450 μg subcutaneously followed by 3 × 225 μg subcutaneously), seven involved human leukocyte antigen (HLA) type, all of which identified improvement/absence of worsening of disease parameters in DR4+ patients and worsening/absence of improvement in DR4− patients. This association with DR4+ and non-DR3 was confirmed using the endpoints normalized area under the curve C-peptide from mixed meal tolerance tests where presence of DR4 HLA haplotype was associated with an improvement in both endpoints. Exploratory immune analysis showed that IMCY-0098 dose B (150 μg subcutaneously followed by 3 × 75 μg subcutaneously) and dose C led to an increase in presumed/potentially protective antigen-specific cytolytic CD4+ T cells and a decrease in pathogenic CD8+ T cells, consistent with the expected mechanism of action of IMCY-0098. The analysis identified significant associations between immune and clinical responses to IMCY-0098. Conclusions: Promising preliminary efficacy results support the design of a phase 2 study of IMCY-0098 in patients with recent-onset T1D. Trial registration: ClinicalTrials.gov NCT03272269; EudraCT: 2016–003514-27.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Korrespondenzautor
Schlagwörter Beta Cells ; Exploratory Analysis ; Immune Biomarker Machine Learning ; Immunotherapy ; T Cells ; Type 1 Diabetes; T-cells
ISSN (print) / ISBN 1741-7015
e-ISSN 1741-7015
Zeitschrift BMC Medicine
Quellenangaben Band: 22, Heft: 1, Seiten: , Artikelnummer: 259 Supplement: ,
Verlag BioMed Central
Verlagsort Campus, 4 Crinan St, London N1 9xw, England
Nichtpatentliteratur Publikationen
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Diabetes Research Type 1 (IDF)
Förderungen Walloon Region, Belgium
EU FP7 program
Imcyse S.A. (Liege, Belgium)