An Asymptotic Analysis of Bivalent Monoclonal Antibody-Antigen Binding
원문 초록
Ligand-receptor interactions are fundamental to many biological processes. For example in antibody-based immunotherapies, the dynamics of an antibody binding with its target antigen directly influence the potency and efficacy of monoclonal antibody (mAb) therapies. In this paper, we present an asymptotic analysis of an ordinary differential equation (ODE) model of bivalent antibody-antigen binding in the context of mAb cancer therapies, highlighting the added complexity associated with bivalency of the antibody. To understand what drives the complex temporal dynamics of bivalent antibody-antigen binding, we construct asymptotic approximations to the model's solutions at different timescales and antibody concentrations that are in good agreement with numerical simulations of the full model. We show how the dynamics differ between two scenarios; a region where unbound antigens are abundant, and one where the number of unbound antigens is small such that the dominant balance within the model equations changes. Of particular importance to the potency and efficacy of mAb treatments are the values of quantities such as antigen occupancy and bound antibody number. We use the results of our asymptotic analysis to approximate the long-time values of these quantities that could be combined with experimental data to facilitate parameter estimation.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Identifying Drift, Diffusion, and Causal Structure from Temporal Snapshots
Analytic estimation of parameters of stochastic volatility diffusion models with exponential-affine characteristic function for currency option pricing
A Simple Approximate Bayesian Inference Neural Surrogate for Stochastic Petri Net Models
Robust Spatiotemporal Epidemic Modeling with Integrated Adaptive Outlier Detection
IMC-PINN-FE: A Physics-Informed Neural Network for Patient-Specific Left Ventricular Finite Element Modeling with Image Motion Consistency and Biomechanical Parameter Estimation
Adjustment for Confounding using Pre-Trained Representations
토론
이 논문과 연결된 포럼 글이 아직 없습니다.