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Optimal control of innate immune response

机译：固有免疫反应的最佳控制

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Treatment of a pathogenic disease process is interpreted as the optimal control of a dynamic system. Evolution of the disease is characterized by a non-linear, fourth-order ordinary differential equation that describes concentrations of pathogens, plasma cells, and antibodies, as well as a numerical indication of patient health. Without control, the dynamic model evidences sub-clinical or clinical decay, chronic stabilization, or unrestrained lethal growth of the pathogen, depending on the initial conditions for the infection. The dynamic equations are controlled by therapeutic agents that affect the rate of change of system variables. Control histories that minimize a quadratic cost function are generated by numerical optimization over a fixed time interval, given otherwise lethal initial conditions. Tradeoffs between cost function weighting of pathogens, organ health, and use of therapeutics are evaluated. Optimal control solutions that defeat the pathogen and preserve organ health are demonstrated for four different approaches to therapy. It is shown that control theory can point the way toward new protocols for treatment and remediation of human diseases.
机译：病原性疾病过程的治疗被解释为动态系统的最佳控制。该疾病的演变特征在于非线性的四阶常微分方程，该方程描述了病原体，浆细胞和抗体的浓度，以及患者健康状况的数字指标。在没有控制的情况下，动态模型会证明亚临床或临床衰变，慢性稳定或病原体不受限制的致死生长，这取决于感染的初始条件。动态方程由影响系统变量变化率的治疗剂控制。在给定致命的初始条件下，通过在固定时间间隔内进行数值优化来生成使二次成本函数最小化的控制历史记录。评估了病原体的成本函数权重，器官健康和治疗方法之间的权衡。针对四种不同的治疗方法，证明了可以击败病原体并保持器官健康的最佳控制解决方案。结果表明，控制理论可以为治疗和治疗人类疾病的新方案指明道路。

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