Quantitative Systems Pharmacology Model of Sickle Cell Disease and Response to Gene Editing Therapy to Support Clinical Development of SAR445136 (BIVV003)

Sickle cell disease (SCD) is caused by a mutation in the β-globin gene that produces abnormal hemoglobin (HbS), leading to clinical manifestations such as painful vaso-occlusive crises, anemia, and shortened lifespan due to organ damage. SAR445136 (BIVV003) is a zinc finger nuclease ex vivo gene editing therapy in Ph1/2 clinical development for treatment of SCD (PRECIZN-1; NCT03653247). SAR445136 targets the erythroid specific enhancer (ESE) region of the transcription factor BCL11A, which controls the switch from fetal hemoglobin (HbF) to adult forms (HbA in healthy subjects and HbS in SCD subjects). By expressing increased levels of HbF, SAR445136-edited cell progeny exhibit reduced HbS polymerization which is expected to ameliorate RBC sickling and the SCD phenotype.

To better understand the dynamics and variability of clinical response to SAR445136, we developed a Quantitative Systems Pharmacology (QSP) model of SCD to describe both key elements of disease biology and the mechanism of action of SAR445136. The QSP approach provides a cohesive representation of the key disease processes in SCD by leveraging additional data sources (e.g. published and internal, clinical and preclinical) to complement data from ongoing clinical trials. The QSP model is applied to help assess mechanism-related questions, such as the observed inter-patient variability with respect to SAR445136 cellular dose, indels, and induced HbF and F cells.

To explore the clinical factors that could influence the response to SAR445136, we centered the structure of the QSP model on a realistic representation of erythropoiesis that can describe hematopoietic stem and progenitor cells and erythroid progenitors in the bone marrow and the periphery, including regulation by cytokines EPO, IL-3, and stem cell factor (SCF) (Figure 1A). We first confirmed that the model recapitulates published bone marrow aspirate and blood cell sorting data from healthy individuals (Figure 1B). Next, we modified the model to describe stress erythropoiesis in SCD by incorporating published data on clinical, natural history, and in vitro assessments of SCD progenitor cells, and the resulting reticulocyte and erythrocyte levels (Figure 1B). The updated model describes key features of the SCD disease state, including reduced lifespan of HbS erythrocytes, elevated plasma reticulocytes (Steinberg MH, et al. Blood. 1997;89: 1078-1088), and altered levels of erythroid progenitors (Hoss SE, et al. Haematologica. 2020 Aug 27. doi: 10.3324/haematol.2020.265462) and cytokines, as well as the protective effects of endogenous HbF.

Finally, we applied the SCD erythropoiesis model to describe the mechanism of action of SAR445136 by representing ablation followed by the introduction of CD34+ cells containing indels with enhanced HbF expression. The model captures the SAR445136 clinical data and simulates the therapeutic effects of increased total Hb and increased proportion of HbF due to the progeny of SAR445136 cells (Figure 1C). The model provides a quantitative framework for evaluating the effects of treatment parameters including cellular dose, mobilization and engraftment variability, indel quality (i.e., variable editing and HbF expression in erythroid progeny [Lessard S, et al. Blood. 2019;134(Supplement_1):97]) and assessing the pan-cellularity of the response. Due to its mechanistic structure, the model also enables exploration of inter-patient variability in terms of cytokine effects on erythropoiesis.

In summary, the QSP model is a computational tool to provide mechanistic insight into emerging SAR445136 clinical data in the context of current understanding of SCD disease biology. The model is intended to provide both qualitative and quantitative support for the clinical development and competitive differentiation of SAR445136. For future development, the model can be expanded to include additional data representing the SCD bone marrow microenvironment to further explore patient heterogeneity.

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