Massinissa Beldjenna (1, 2 – current affiliation), Glenn Gauderat (1), Sylvain Fouliard (1).
(1) Translational Pharmacometrics, Quantitative Pharmacology, Servier, (2) System Pharmacology and Pharmacy, Leiden Academic Centre for Drug Research (LACDR), Leiden University.
Introduction: CD40 is a transmembrane protein expressed by several immune cells [1] and plays a central role in a variety of immune responses [2]. CD40 antagonism was explored in several clinical studies in autoimmune diseases [3, 4, 5]. Extensive results were published for Iscalimab, an anti-CD40 therapeutic monoclonal antibody [5, 6]. Correlations were observed between CD40 antagonism and other immune system endpoints such as percentage of CD69-positive B cells [5] or CXCL13 concentration [6].
This pool of data can be used to characterize the dynamics and abundance of the target, as well as the clinical and biological impact of its antagonism. Yet, there is currently no published mechanistic model of response to anti-CD40 treatments. Such a model would offer a better understanding of target behavior to better design anti-CD40 compounds and combinations, for a more effective treatment of associated autoimmune diseases. Thus, we developed a multi-endpoint PK/TE/PD model describing CD40 antagonism and its effect on other biological endpoints.
Objectives:
• Use available PK/PD and mechanistic data to build a comprehensive TMDD multi-endpoint model of CD40 antagonism with Iscalimab.
• Use modelling to formulate hypothesis for the release of soluble CD40 after Iscalimab administration.
• Propose models for the relationship between target engagement and downstream biomarkers, especially immune response to vaccination.
Methods: We used published data for CD40 antagonism with Iscalimab, that cover a wide range of doses (0.03 to 30 mg/kg), for single and repeated administrations of IV and SC boluses, in individuals with different disease status (healthy subjects, patients with rheumatoid arthritis or Sjögren’s syndrome). Data were digitized from literature [5, 6].
The model was built sequentially and features:
1) A linear PK model describing the distribution and non-specific catabolic elimination, built with PK data at high concentrations,
2) A TMDD model capturing Iscalimab engagement with membrane CD40 built through adjunction in the previous dataset of PK data over the lower range of concentrations, and expression of free and total CD40 on B cells,
3) A two targets TMDD model with both membrane and soluble CD40, built through adjunction in the previous dataset of total soluble CD40.
The final TMDD model was fitted simultaneously with those four observables. PK and target engagement parameters were then fixed for the rest of the study.
4) A PK/TE/PD model linking membrane CD40 concentration to distal PD endpoints: percentage of CD69 positive B cells, CXCL13 concentration, anti-KLH IgG concentration after vaccination.
Model selection and performance assessment were conducted using statistical testing (likelihood ratio tests, AIC and BIC comparisons), goodness of fit (conditional weighted residuals and visual predictive checks) and biological plausibility.
Data were digitized with Engauge and processed with R, and parameter estimation was performed with NONMEM using the Laplacian method.
Results: A quasi-equilibrium approximation of TMDD for two targets with a shared dissociation constant properly described Iscalimab concentration, free and total CD40 on B cells, and total soluble CD40. A transit compartment model recycling membrane Iscalimab-CD40 complex and releasing it as soluble complex allowed for the best fit.
Percentage of CD69-positive B cells and CXCL13 concentration were well captured with a sigmoidal direct effect model and a turnover model respectively. Anti-KLH IgG concentration after vaccination was well captured with a modified transit compartment model, with time events to represent vaccination time and transcription delay.
We observed satisfactory convergence for all estimates (RSE<30%, except 50% for the Hill coefficient), and they were all in agreement with published literature data [7, 8, 9] and prior in vitro studies [10].
Conclusion: A multi-endpoint PK/PD model integrating the interplay between PK, membrane and soluble target binding, and several biomarkers has been successfully developed and allows to simulate the modulation of several biomarkers after administration of anti-CD40 treatment.
This constitutes a first extensive mechanistic model regarding CD40 antagonism that can be used to determine optimal dosing regimens. This first model could be improved by conducting a meta-study with other CD40 antagonists, or using individual data in order to properly characterize variability and further identify covariates.
References:
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Reference: PAGE 32 (2024) Abstr 10898 [www.page-meeting.org/?abstract=10898]
Poster: Drug/Disease Modelling - Other Topics