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

Chaudhury, Anwesha; Zhu, Xu; Chu, Lulu; Goliaei, Ardeshir; June, Carl H.; Kearns, Jeffrey D.; Stein, Andrew M.

doi:10.1002/jcph.1691

Cited by 38 publications

(53 citation statements)

References 60 publications

(102 reference statements)

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“…Our results point to the importance of the immune system's influence on CAR T cell kinetics, and the impact of those kinetics on potentially stochastic tumour dynamics. We hope that our model can be consolidated with descriptions of short-term changes in inflammatory cytokines [19,[39][40][41], because these are accessible alternative biomarkers for the immune system's impact [11]. On the other hand, engineering a CAR T product with fewer cell divisions, improving its 'stemness' or increasing metabolic capacity of CAR T cells should lead to a higher carrying capacity.…”

Section: Discussionmentioning

confidence: 99%

“…In the context of timing of events, our model can be useful to test new treatment strategies in silico, to inform clinical trial design. For example, we used our model to inform the timing of a second infusion, with or without additional lymphodepletion (electronic supplementary material, section 6) [11]. To improve outcomes with a second infusion, lymphodepletion that resets the T cells is necessary.…”

Section: (G) Necessity Of Lymphodepletionmentioning

confidence: 99%

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The roles of T cell competition and stochastic extinction events in chimeric antigen receptor T cell therapy

Kimmel¹,

Locke²,

Altrock

2021

Proc. R. Soc. B.

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Chimeric antigen receptor (CAR) T cell therapy is a remarkably effective immunotherapy that relies on in vivo expansion of engineered CAR T cells, after lymphodepletion (LD) by chemotherapy. The quantitative laws underlying this expansion and subsequent tumour eradication remain unknown. We develop a mathematical model of T cell–tumour cell interactions and demonstrate that expansion can be explained by immune reconstitution dynamics after LD and competition among T cells. CAR T cells rapidly grow and engage tumour cells but experience an emerging growth rate disadvantage compared to normal T cells. Since tumour eradication is deterministically unstable in our model, we define cure as a stochastic event, which, even when likely, can occur at variable times. However, we show that variability in timing is largely determined by patient variability. While cure events impacted by these fluctuations occur early and are narrowly distributed, progression events occur late and are more widely distributed in time. We parameterized our model using population-level CAR T cell and tumour data over time and compare our predictions with progression-free survival rates. We find that therapy could be improved by optimizing the tumour-killing rate and the CAR T cells' ability to adapt, as quantified by their carrying capacity. Our tumour extinction model can be leveraged to examine why therapy works in some patients but not others, and to better understand the interplay of deterministic and stochastic effects on outcomes. For example, our model implies that LD before a second CAR T injection is necessary.

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Section: Discussionmentioning

confidence: 99%

Section: (G) Necessity Of Lymphodepletionmentioning

confidence: 99%

The roles of T cell competition and stochastic extinction events in chimeric antigen receptor T cell therapy

Kimmel¹,

Locke²,

Altrock

2021

Proc. R. Soc. B.

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“…A recent review of mathematical models of CAR T-cell therapy [25] suggested a number of requisites that any of these models should include to provide a faithful description of the biological dynamics. The model presented here succeeds in recapitulating antigendriven expansion, bi-exponential decay, and a limited expansion despite large antigen burden.…”

Section: Discussionmentioning

confidence: 99%

“…Like animal models, mathematical models offer a simplified representation of a system, providing a tool to explore causal relations and mechanisms. As a recent therapeutic breakthrough, CAR T therapy is starting to lend itself to a mathematical characterization [25]. While there are some studies involving solid tumors [26,27], most focus on hematological malignancies, given the success obtained in this group of cancers.…”

Section: Introductionmentioning

confidence: 99%

A Mathematical Description of the Bone Marrow Dynamics during CAR T-Cell Therapy in B-Cell Childhood Acute Lymphoblastic Leukemia

Martínez-Rubio

Chulián

Goñi

et al. 2021

IJMS

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Chimeric Antigen Receptor (CAR) T-cell therapy has demonstrated high rates of response in recurrent B-cell Acute Lymphoblastic Leukemia in children and young adults. Despite this success, a fraction of patients’ experience relapse after treatment. Relapse is often preceded by recovery of healthy B cells, which suggests loss or dysfunction of CAR T-cells in bone marrow. This site is harder to access, and thus is not monitored as frequently as peripheral blood. Understanding the interplay between B cells, leukemic cells, and CAR T-cells in bone marrow is paramount in ascertaining the causes of lack of response. In this paper, we put forward a mathematical model representing the interaction between constantly renewing B cells, CAR T-cells, and leukemic cells in the bone marrow. Our model accounts for the maturation dynamics of B cells and incorporates effector and memory CAR T-cells. The model provides a plausible description of the dynamics of the various cellular compartments in bone marrow after CAR T infusion. After exploration of the parameter space, we found that the dynamics of CAR T product and disease were independent of the dose injected, initial B-cell load, and leukemia burden. We also show theoretically the importance of CAR T product attributes in determining therapy outcome, and have studied a variety of possible response scenarios, including second dosage schemes. We conclude by setting out ideas for the refinement of the model.

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“…The biological determinants of inter‐individual variation in CK profiles, antitumor activity and safety (eg, cytokine release) are multifactorial and a consequence of complex interplay of several host and tumor‐related factors. Chaudhury et al outline a question‐based value proposition for model‐informed design (eg, CAR affinity and expression optimization) and development (eg, dose selection/optimization) of CAR‐T therapies 41 . In addition to a detailed treatment of the taxonomy of CAR‐T cellular kinetic‐dynamic model structures and their performance characteristics, the authors offer a forward‐looking perspective and future directions for quantitative translational research in this area to advance model development and applications.…”

mentioning

confidence: 99%

Role of Physiologically Based Pharmacokinetic Modeling and Simulation in Enabling Model‐Informed Development of Drugs and Biotherapeutics

Arya

Venkatakrishnan

2020

The Journal of Clinical Pharma

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

Cited by 38 publications

References 60 publications

The roles of T cell competition and stochastic extinction events in chimeric antigen receptor T cell therapy

The roles of T cell competition and stochastic extinction events in chimeric antigen receptor T cell therapy

A Mathematical Description of the Bone Marrow Dynamics during CAR T-Cell Therapy in B-Cell Childhood Acute Lymphoblastic Leukemia

Role of Physiologically Based Pharmacokinetic Modeling and Simulation in Enabling Model‐Informed Development of Drugs and Biotherapeutics

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