Anastasios Siokis (1), Britta Wagenhuber (1), Lieselot Bontinck (2), Annemie Deiteren (2), Benjamin Suratt (3), Heribert Staudinger (4)
(1) Sanofi R&D, Frankfurt am Main, Germany, (2) Sanofi R&D, Ghent, Belgium, (3) Sanofi R&D, Cambridge, MA, USA, (4) Sanofi R&D, Bridgewater, NJ, USA
Introduction: Asthma is a heterogenous disease that affects millions of people worldwide. Despite the availability of multiple treatment options, a significant proportion of patients either fails to respond adequately to existing treatments or experiences diminishing therapeutic effects over time. This highlights the need for innovative treatments.
Objectives: We apply mechanistic quantitative systems pharmacology (QSP) modeling to support the accelerated development of lunsekimig, a novel bispecific anti-thymic stromal lymphopoietin (TSLP)/anti-interleukin (IL)-13 NANOBODY®* construct
(*NANOBODY® is a registered trademark of Sanofi or an affiliate).
Methods: We have developed a mechanistic QSP model describing the type-2 pathophysiology of asthma, where different cell types, such as Th2 cells, B cells and eosinophils, as well as cytokines, such as IL4, IL5 and IL13, play a central role – not only in the development of asthma, but also in its progression into a chronic respiratory condition. In the model, we account for cell-cell and cell-cytokine interactions. Cells produce cytokines when stimulated and migrate between different compartments, such as lymph nodes and lung. In addition, the cytokines present in the model drive the production of chemokines (e.g., CCL17, CCL26) and proteins (e.g., periostin) that are used as asthma biomarkers.
The model covers the pharmacology of asthma biologics with distinct modes of action and has been calibrated with diverse data, such as preclinical in-vitro and in-vivo animal and human data as well as clinical data obtained from published Phase 2 clinical trials conducted in asthma for dupilumab (anti-IL4Ra) [1], mepolizumab (anti-IL-5) [2], lebrikizumab (anti-IL-13) [3], oxelumab (anti-OX40L) [4], and tezepelumab (anti-TSLP) [5]. For model validation, published data from dupilumab [6], mepolizumab [7], lebrikizumab [8] and tezepelumab [9] Phase 3 clinical trials in asthma patients have been used.
Leveraging the presented QSP model, we generated virtual asthma patients. Diverse sources of uncertainty and variability are used. On one hand, we account for uncertainties in drug-target affinities (kD) arising from in-vitro/in-vivo measurements, together with the inter-individual variability (IIV) observed in the PK profiles from published popPK models. On the other hand, a collection of biologically relevant parameters of the QSP model arising from local and global sensitivity analyses are selected.
Altogether, the selected parameters are perturbed from the average patient based on different distributions (e.g. normal, lognormal), with inclusion/exclusion criteria applied to exclude unrealistic virtual patients or patients that did not match the criteria of the simulated clinical trials.
The QSP model with virtual patients accurately predicts the effects of the above-mentioned compounds and their diverse mechanisms of action, especially when considering tezepelumab and the TSLP axis as well as lebrikizumab and the IL-13 axis, both targets of lunsekimig.
Results: The presented model has been used to predict the outcome of the first-in-human (FIH) proof-of-mechanism (PoM) single dose study of lunsekimig in asthma patients (NCT05366764 funded by Sanofi). The model accurately predicted the treatment effect of lunsekimig on blood biomarkers (eosinophils, IgE) and endpoints (FeNO).
In addition, we performed in-silico head-to-head clinical trials to compare the treatment effect of lunsekimig versus tezepelumab and lebrikizumab, both biologics tested in asthma. Finally, the model facilitated the design and dose regimen selection that enabled the direct transition of lunsekimig from a single-dose phase 1b to a dose-ranging phase 2b study.
Conclusions: The in-silico head-to-head comparisons using virtual patients empowered by the asthma QSP model complemented the FIH PoM data to support the early Proof of Concept for lunsekimig and were integral in accelerating its transition from FIH directly to phase 2b clinical development.
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[9] Menzies-Gow A, Corren J, Bourdin A, Chupp G, Israel E, Wechsler ME, et al. Tezepelumab in Adults and Adolescents with Severe, Uncontrolled Asthma. N Engl J Med. 2021;384(19):1800-9.
Reference: PAGE 32 (2024) Abstr 10874 [www.page-meeting.org/?abstract=10874]
Poster: Drug/Disease Modelling - Other Topics