Title: On Drug Delivery System Parameter Optimisation via Semantic Information Theory Show Chinese title

Title: 通过语义信息论进行药物递送系统参数优化

Abstract: We investigate the application of semantic information theory to drug delivery systems (DDS) within the molecular communication (MC) framework. To operationalise this, we observe a DDS as a molecular concentration-based channel. Semantic information is defined as the amount of information required for a DDS to achieve its therapeutic goal in a dynamic environment. We derive it by introducing interventions, defined as modifications to DDS parameters, a viability function, and system-environment correlations quantified via the channel capacity. Here, the viability function represents DDS performance based on a drug dose-response relationship. Our model considers a system capable of inducing functional changes in a receiver cancer cell, where exceeding critical DDS parameter values can significantly reduce performance or cost-effectiveness. By analysing the MC-based DDS model through a semantic information perspective, we examine how correlations between the internalised particle concentration $(Y)$ and the particle concentration in the extracellular environment $(X)$ evolve under interventions. The final catalogue of results provides a quantitative basis for DDS design and optimisation, offering a method to determine optimal DDS parameter values under constraints such as chemical budget, desired effect and accuracy. Thus, the proposed framework can serve as a novel tool for guiding DDS design and optimisation. Show Chinese abstract

Abstract: 我们研究语义信息论在分子通信（MC）框架内药物输送系统（DDS）中的应用。 为了实现这一点，我们将DDS观察为一种基于分子浓度的信道。 语义信息被定义为DDS在动态环境中实现其治疗目标所需的信息量。 我们通过引入干预措施（定义为DDS参数的修改）、生存函数以及通过信道容量量化系统与环境的相关性来推导它。 在这里，生存函数基于药物剂量反应关系表示DDS的性能。 我们的模型考虑了一个能够在接收癌细胞中诱导功能变化的系统，其中超过临界DDS参数值会显著降低性能或成本效益。 通过语义信息的角度分析基于MC的DDS模型，我们研究了在干预下内部化粒子浓度$(Y)$与细胞外环境中粒子浓度$(X)$之间的相关性如何演变。 最终的结果清单为DDS的设计和优化提供了定量基础，提供了一种在化学预算、期望效果和准确性等约束条件下确定最优DDS参数值的方法。 因此，所提出的框架可以作为指导DDS设计和优化的新工具。