Mathematical deconvolution of CAR T-cell proliferation and exhaustion from real-time killing assay data

Sahoo, Prativa; Yang, Xin; Abler, Daniel; Maestrini, Davide; Adhikarla, Vikram; Frankhouser, David; Cho, Heyrim; Machuca, Vanessa; Wang, Dongrui; Barish, Michael E.; Gutova, Margarita; Branciamore, Sergio; Brown, Christine E.; Rockne, Russell

doi:10.1101/786020

Cited by 9 publications

(20 citation statements)

References 46 publications

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“…In other words, the CAR‐T cell and tumor cell populations oscillate indefinitely, as illustrated in Figure 2C. This cyclic behavior is also observed in more complex models, for example, when the tumor growth equation is described by Gompertz or logistic growth instead 19,20 . To our knowledge, this cyclic behavior has never been observed in the clinic, and therefore a cellular kinetic‐pharmacodynamic model should not exhibit these cycles.…”

Section: Cellular Kinetic‐pharmacodynamic Modelsmentioning

confidence: 68%

“…Large, unrealistic limit cycles are absent : Some models predict cyclic behavior of the CAR‐T cells and tumor cells (see Figure 3C), 19,20 which, to our knowledge, has not been observed in the clinic for CAR‐T cell therapy, and so the model also should not produce this behavior when used to characterize patient data.…”

Section: Cellular Kinetic‐pharmacodynamic Modelsmentioning

confidence: 94%

“…But here we require the property that CAR‐T cell expansion be limited. Accommodates multiple doses : To explore a range of dosing regimens, models should accommodate multiple doses of CAR‐T cells. All models in Table 2 can accommodate multiple doses, although the models with proliferation up to time T max require a cascade model structure for this effect (see Supplemental Figure S1). Large, unrealistic limit cycles are absent : Some models predict cyclic behavior of the CAR‐T cells and tumor cells (see Figure 3C), 19,20 which, to our knowledge, has not been observed in the clinic for CAR‐T cell therapy, and so the model also should not produce this behavior when used to characterize patient data.…”

Section: Cellular Kinetic‐pharmacodynamic Modelsmentioning

confidence: 99%

See 2 more Smart Citations

Chimeric Antigen Receptor T Cell Therapies: A Review of Cellular Kinetic‐Pharmacodynamic Modeling Approaches

Chaudhury¹,

Zhu

Chu³

et al. 2020

The Journal of Clinical Pharma

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Chimeric antigen receptor T cell (CAR-T cell) therapies have shown significant efficacy in CD19+ leukemias and lymphomas. There remain many challenges and questions for improving next-generation CART cell therapies, and mathematical modeling of CART cells may play a role in supporting further development. In this review, we introduce a mathematical modeling taxonomy for a set of relatively simple cellular kinetic-pharmacodynamic models that describe the in vivo dynamics of CART cell and their interactions with cancer cells. We then discuss potential extensions of this model to include target binding, tumor distribution, cytokine-release syndrome, immunophenotype differentiation, and genotypic heterogeneity. Keywords cellular kinetic-pharmacodynamic model, chimeric antigen receptor-T cell (CAR-T cell) therapy, model-informed drug development (MIDD), quantitative systems pharmacology (QSP)

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Section: Cellular Kinetic‐pharmacodynamic Modelsmentioning

confidence: 68%

Section: Cellular Kinetic‐pharmacodynamic Modelsmentioning

confidence: 94%

Section: Cellular Kinetic‐pharmacodynamic Modelsmentioning

confidence: 99%

See 1 more Smart Citation

Chimeric Antigen Receptor T Cell Therapies: A Review of Cellular Kinetic‐Pharmacodynamic Modeling Approaches

Chaudhury¹,

Zhu

Chu³

et al. 2020

The Journal of Clinical Pharma

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“…Several computational models have recently been developed to investigate aspects of CAR T-cell therapy including cytokine release syndrome toxicity management (Hopkins et al, 2018;Stein et al, 2017Stein et al, , 2019, mechanisms of CAR T-cell activation (Harris et al, 2018;Rohrs et al, 2019), and how factors including CAR T-cell dose, donor-dependent T-cell differences, cancer cell proliferation, and target antigen expression contribute to the overall effectiveness of CAR T-cell therapy (Hardiansyah and Ng, 2019;Kimmel et al, 2019;Rodrigues et al, 2019;Sahoo et al, 2020). Here we formulate a model that allows us to investigate how the interplay between specific preconditioning plans and CAR T-cell dosage affects patient outcomes.…”

Section: Mathematical Modeling Of Cancer Treatmentmentioning

confidence: 99%

Modelling CAR T-cell Therapy with Patient Preconditioning

Owens

Božić

2020

Preprint

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The Federal Drug Administration (FDA) approved the first Chimeric Antigen Receptor T-cell (CAR T-cell) therapies for the treatment of several blood cancers in 2017, and efforts are underway to broaden CAR T technology to address other cancer types. Standard treatment protocols incorporate a preconditioning regimen of lymphodepleting chemotherapy prior to CAR T-cell infusion. However, the connection between preconditioning regimens and patient outcomes is still not fully understood. Optimizing patient preconditioning plans and reducing the CAR T-cell dose necessary for achieving remission could make therapy safer. In this paper, we test treatment regimens consisting of sequential administration of chemotherapy and CAR T-cell therapy on a system of differential equations that models the tumor-immune interaction. We use numerical simulations of treatment plans from within the scope of current medical practice to assess the effect of preconditioning plans on the success of CAR T-cell therapy. Model results affirm clinical observations that preconditioning can be crucial for some patients, not just to reduce side effects, but to even achieve remission at all. We demonstrate that preconditioning plans using the same CAR T-cell dose and the same total concentration of chemotherapy can lead to different patient outcomes due to different delivery schedules. Results from sensitivity analysis of the model parameters suggest that making small improvements in the effectiveness of CAR T-cells in attacking cancer cells, rather than targeting the recruitment and longevity of CAR T-cells, will significantly reduce the minimum dose required for successful treatment. Our modeling framework represents a starting point for evaluating the efficacy of patient preconditioning in the context of CAR T-cell therapy.

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“…Mathematical models can disentangle complex systems, such as those arising in mutually interacting immunity, tumour growth, and immunotherapy and have been used extensively for that purpose in the last few years (see e.g., the reviews [21][22][23][24][25][26][27]). Some recent mathematical modelling studies have been carried out to study different aspects of CAR-T cell therapies [28][29][30][31][32][33][34][35]. In this paper we study, in silico, using a mathematical model, the response of a solid tumour to a dual CAR-T product targetting both CD19 and a tumour-associated antigen.…”

Section: Introductionmentioning

confidence: 99%

Dual-Target CAR-Ts with On- and Off-Tumour Activity May Override Immune Suppression in Solid Cancers: A Mathematical Proof of Concept

León-Triana

Pérez‐Martínez

Ramírez-Orellana

et al. 2021

Cancers

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Chimeric antigen receptor (CAR)-T cell-based therapies have achieved substantial success against B-cell malignancies, which has led to a growing scientific and clinical interest in extending their use to solid cancers. However, results for solid tumours have been limited up to now, in part due to the immunosuppressive tumour microenvironment, which is able to inactivate CAR-T cell clones. In this paper we put forward a mathematical model describing the competition of CAR-T and tumour cells, taking into account their immunosuppressive capacity. Using the mathematical model, we show that the use of large numbers of CAR-T cells targetting the solid tumour antigens could overcome the immunosuppressive potential of cancer. To achieve such high levels of CAR-T cells we propose, and study computationally, the manufacture and injection of CAR-T cells targetting two antigens: CD19 and a tumour-associated antigen. We study in silico the resulting dynamics of the disease after the injection of this product and find that the expansion of the CAR-T cell population in the blood and lymphopoietic organs could lead to the massive production of an army of CAR-T cells targetting the solid tumour, and potentially overcoming its immune suppression capabilities. This strategy could benefit from the combination with PD-1 inhibitors and low tumour loads. Our computational results provide theoretical support for the treatment of different types of solid tumours using T cells engineered with combination treatments of dual CARs with on- and off-tumour activity and anti-PD-1 drugs after completion of classical cytoreductive treatments.

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Mathematical deconvolution of CAR T-cell proliferation and exhaustion from real-time killing assay data

Cited by 9 publications

References 46 publications

Chimeric Antigen Receptor T Cell Therapies: A Review of Cellular Kinetic‐Pharmacodynamic Modeling Approaches

Chimeric Antigen Receptor T Cell Therapies: A Review of Cellular Kinetic‐Pharmacodynamic Modeling Approaches

Modelling CAR T-cell Therapy with Patient Preconditioning

Dual-Target CAR-Ts with On- and Off-Tumour Activity May Override Immune Suppression in Solid Cancers: A Mathematical Proof of Concept

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