Differential Scanning Calorimetry (DSC): An Invaluable Tool for the Thermal Evaluation of Advanced Chimeric Liposomal Drug Delivery Nanosystems

差示扫描量热法 脂质体 热致晶体 药物输送 表征(材料科学) 材料科学 纳米技术 化学 生物医学工程 聚合物 有机化学 热力学 工程类 物理 液晶
作者
Maria Chountoulesi,Nikolaos Naziris,Νatassa Pippa,Stergios Pispas,Costas Demetzos
出处
期刊:Series in bioengineering [Springer International Publishing]
卷期号:: 297-337 被引量:13
标识
DOI:10.1007/978-981-13-0989-2_9
摘要

Chimeric liposomal systems are classified as advanced drug delivery nanosystems, being composed of different kinds of biomaterials, such as phospholipids and polymers. Chimeric liposomes present many advantages, compared to conventional ones, such as great functionality, stimuli-responsiveness and increased targeting to the pathological tissue. Among the analytical techniques established for the liposomal system characterization, Differential Scanning Calorimetry (DSC) is applied to indicate their thermotropic behavior and thermal stability, providing useful information, in order to optimize the quality and therapeutic efficiency of the liposomal formulations. Until very recently, several researches have aimed at explaining the behavior of carrier lipid forms by the DSC method. Therefore, DSC has been quite frequently applied in pharmaceutical research for scanning the thermal behavior of the samples and to record the difference between the heat flows, while it provides quick and accurate information about the physical and energetic parts of a material. In the present chapter, a variety of different chimeric liposomal systems is presented that were analyzed in terms of their thermal behavior, describing the utilized DSC protocols and highlighting the interpretation of the DSC results. The aim of this chapter is to prove, through different literature examples of chimeric liposomal systems, the utility of the DSC technique upon the characterization of their thermotropic behavior which is strictly correlated with the interactions and cooperativity of the different biomaterials, as well as how it predicts the efficacy of the examined liposomal platforms.
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