如何在药物研发的早期对候选药物诱发磷脂沉积（DIPLD）的风险进行有效的预测是新药研发中一个亟待解决的问题。人工模拟细胞膜色谱法（ACMC）用于药物DIPLD风险的筛选具有操作简单、花费低廉、自动化程度高和易于推广等优点，在新药研发中具有广泛的应用前景。我们在前期工作中对脂质体电动色谱和磷脂膜整体色谱柱进行了系统的研究，结果显示，这些ACMC系统能有效地预测一些与药物磷脂作用相关的药理作用。本课题拟首次采用ACMC方法模拟溶酶体磷脂层膜环境，对药物DIPLD风险进行预测和筛选研究，同时还将对酸性磷脂成分在DIPLD过程中的重要性以及药物立体结构与DIPLD风险之间的构效关系进行研究。本课题的意义不仅在于首次探讨色谱模型预测药物DIPLD风险的可行性，而且在于其将对药物磷脂作用抑制磷脂酶活性的DIPLD机理提供强有力的支持，因此在解决新药研发中有关DIPLD的问题具有重要的现实和理论意义。

Drug-induced phospholipidosis (DIPLD), which is an FDA recognized potentially adverse response, represents a potential major liability for compounds transitioning between the drug discovery and development phases, prior to entering final regulatory approval. Consequently, it is highly desirable to identify any potential liability to induce PLD as early as possible in the research phase, prior to candidates entering expensive development. The reason for PLD is believed to be the formation of drug-phospholipid complexes, which cannot be subsequently metabolized by phospholipid-degrading enzymes.This mechanism has been utilized for developing early screening tool for DIPLD potential of drug candidates. Chromatographic techniques we have been developing hold great potential for studying DIPLD compound liabilities, since they can effectively mimic drug-membrane interactions in an in vitro analytical environment. Artificial cell membrane chromatography (ACMC), such as immobilized artificial membrane chromatography (IAM) and liposome electrokinetic chromatography (LEKC), have been used in estimating membrane affinity related properties of drug candidates, such as intestinal absorption, volume distribution, blood brain barrier permeability. These techniques also offer a fast, reliable, high-throughput and cost-effective screening tool for early prediction of the PLD risk. In this proposal, both LEKC and IAMC were used to mimic the lysosome membrane environment in order to develop an successful PLD screening model. A series of novel monolithic columns containing different phospholipids were first prepared by co-polymerizing specific designed phospholipid containing monomers. The influence of acidic phospholipids on the predictivity was also investigated by varying the type and amount of acidic phospholipids within ACMC system. Additionally, the influence of the running buffer pH and the role of the phospholipid bilayer structure were also studied. The initial results showed that there is a significant correlation between the retention of compounds on the ACMC system and its DIPLD potential. 450 chemicals of which 93 induced PLD and 357 were shown not to induce PLD, were analyzed in this study. The QSAR will be carried out in order to find any key structural features of PLD inducers, and the binding sites between compounds and phospholipids related. This research can provide not only a rapid, robust, reproducible and sensitive in vitro trend analysis for a large number of drug candidates early in the drug discovery process with minimal resources, but also a strong evidence for drug-phospholipid complex formation mechanism of PLD. It has important practical and theoretical significance in solving problems in related to PLD drug development.