抗结核药致肝损伤 (anti-tuberculosis drug-induced hepatic injury, ADIH) 是药源性肝损伤最常见的原因。研究显示NF-κB蛋白活化在ADIH的发生发展过程中起重要作用，而多种海洋类胡萝卜素 (marine carotenoids, MCs) 对NF-κB蛋白活化存在抑制效应，但其能否抑制ADIH及其影响的信号通路分子尚不明确。利用数学模型进行仿真实验以预测ADIH进程及药物干预效果有助于高效地发现损伤变化的规律性，减少人、财、物力消耗，提高实验效率。本项目拟基于NF-κB蛋白寻找ADIH及MCs抗ADIH的关键信号分子，进而建立具有时滞及反馈机制的生理药动/信号转导网络模型，通过抗结核药肝内浓度变化预测其肝毒性，并通过不同给药方案和剂型下MCs的体内过程预测其抗ADIH活性，为ADIH进程预测及药物治疗方案设计提供新的方法。

Anti-tuberculosis drug-induced hepatic injury (ADIH) is the most common cause of drug-induced liver injury. It has shown that NF-κB protein activation plays an important role in the occurrence and development of ADIH, while a variety of marine carotenoids (MCs) have inhibitory effects on NF-κB protein activation, but whether they can inhibit ADIH, as well as the signaling pathway molecules that they affect, are still unclear. The use of mathematical models to perform simulation experiments to predict the ADIH process and the effect of drug interventions is helpful to efficiently discover the regularity of injury changes, reduce labor and material consumption, and improve experimental efficiency. This project aims to find the key signaling molecules of ADIH and MCs against ADIH based on NF-κB protein, and then establish a physiologically-based pharmacokinetic/signal transduction network model with time delay and feedback mechanism, predict the hepatotoxicity of anti-tuberculosis drugs through the change of intrahepatic concentration, and predict the anti-ADIH activity of MCs through the in vivo process under different administration schemes and dosage forms, so as to provide new methods for the prediction of ADIH process and the design of pharmacotherapeutic schemes.