DEVELOPMENT OF A QUANTITATIVE SYSTEMS PHARMACOLOGY (QSP) MODEL FOR SYSTEMIC LUPUS ERYTHEMATOSUS (SLE) FOR THERAPEUTIC EVALUATION IN A VIRTUAL POPULATION

PV261 / #833 Poster Topic: AS24 - SLE-Treatment Background/Purpose Despite numerous recent clinical trials, systemic lupus erythematosus (SLE) has an unmet need with only 2 approved biologics, while other autoimmune conditions have seen an explosion in approvals of targeted therapies. As such, the complex pathogenesis of SLE warrants ongoing efforts for novel therapeutic investigation and mechanistic insights. Quantitative systems pharmacology (QSP) modeling is becoming an integral tool of drug development through combining physiologic, mechanistic disease models with therapeutic exposure-response relationships. By generating a mathematical representation of molecular and cellular mechanisms in a disease, QSP can evaluate therapeutic effects and provide insight into linking clinical endpoints to optimal biological network targets, clinical trial design, and dosing strategies. A QSP model was developed to characterize clinical endpoint data, assess dosing strategies, and compare mechanism of action contribution to disease pathophysiology for a suite of therapies in moderate to severe SLE, including B cell Activating Factor (BAFF) inhibitors, type I interferon (IFN) inhibitors, tyrosine kinase 2 (TYK2) inhibitors, and standards of care. In this study, 2 IFN biologics: anifrolumab, acting upon the IFN receptor, and sifalimumab, acting upon IFN-α, are compared to assess model performance. Methods An ordinary differential equation (ODE)-based QSP model for SLE was constructed to describe the interplay of cells and biomolecules, tissue-level phenomena, and clinical endpoints. These interactions were modeled using literature-reported and internal information from in vitro/ex vivo assay. SLE Responder Index-4 (SRI4), Cutaneous Lupus Erythematosus Disease Area and Severity Index (CLASI), and swollen joint count (SJC) clinical endpoints are included to support clinical evaluation. Thales, a QSP modeling platform designed to streamline optimization of virtual patient populations (SimPops), was utilized to calibrate the model to 45 clinical trials and 29 treatment arms simultaneously, thereby capturing the variability of patients representing a broader SLE population. Anifrolumab trials were included in the model calibration data, while sifalimumab trials were withheld to be used only for model validation. Model assessment was evaluated by quantifying percentage of datapoints that fell within model confidence intervals. Results The model’s calibrated SimPops captures SRI4, CLASI, and SJC profiles within 95% CIs across the various dosing levels of anifrolumab in the training dataset and successfully predicted sifalimumab drug effects in the validation dataset. Notably, the model reproduces clinical endpoint profiles for the trial placebo groups despite differing baseline patient characteristics and tapering protocols across the anifrolumab and sifalimumab trials. Furthermore, the model exhibits a greater SRI4 response at week 52 for anifrolumab when compared to sifalimumab, in agreement with the anifrolumab ( NCT01438489 ) and sifalimumab ( NCT01283139 ) trials. The difference in patient improvement may be attributable to the broader, systemic effects of targeting the IFN receptor as opposed to the IFN-α cytokine alone. Conclusions An SLE QSP model was successfully developed and optimized a SimPops that accurately captures clinical endpoint data for 2 IFN biologics. The Thales platform and QSP model framework allows for efficient addition of clinical trials, biological mechanisms, and therapeutics as new data becomes available, allowing for more robust predictions of novel therapeutics and combinations. Further, key determinants of individual patient response can be explored to identify patient subgroups that are best suited for specific therapies. Overall, the continuously evolving QSP model can serve as a foundation for SLE therapeutic development by providing a mechanistic understanding of SLE.

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