Nguyen Thi-Thao-Linh, Maeng Han-Joo
College of Pharmacy, Gachon University, 191 Hambakmoe-ro, Yeonsu-gu, Incheon 21936, Korea.
Pharmaceutics. 2022 Mar 5;14(3):572. doi: 10.3390/pharmaceutics14030572.
Nose-to-brain drug delivery has been of great interest for the treatment of many central nervous system (CNS) diseases and psychiatric disorders over past decades. Several nasally administered formulations have been developed to circumvent the blood-brain barrier and directly deliver drugs to the CNS through the olfactory and trigeminal pathways. However, the nasal mucosa's drug absorption is insufficient and the volume of the nasal cavity is small, which, in combination, make nose-to-brain drug delivery challenging. These problems could be minimized using formulations based on solid lipid nanoparticles (SLNs) or nanostructured lipid carriers (NLCs), which are effective nose-to-brain drug delivery systems that improve drug bioavailability by increasing drug solubility and permeation, extending drug action, and reducing enzymatic degradation. Various research groups have reported in vivo pharmacokinetics and pharmacodynamics of SLNs and NLCs nose-to-brain delivery systems. This review was undertaken to provide an overview of these studies and highlight research performed on SLN and NLC-based formulations aimed at improving the treatment of CNS diseases such neurodegenerative diseases, epilepsy, and schizophrenia. We discuss the efficacies and brain targeting efficiencies of these formulations based on considerations of their pharmacokinetic parameters and toxicities, point out some gaps in current knowledge, and propose future developmental targets.
在过去几十年中,鼻脑给药一直是治疗许多中枢神经系统(CNS)疾病和精神障碍的研究热点。已经开发了几种鼻腔给药制剂,以绕过血脑屏障,并通过嗅觉和三叉神经途径将药物直接递送至中枢神经系统。然而,鼻黏膜的药物吸收不足,且鼻腔容积小,这两个因素共同导致鼻脑给药具有挑战性。使用基于固体脂质纳米粒(SLNs)或纳米结构脂质载体(NLCs)的制剂可以将这些问题最小化,它们是有效的鼻脑给药系统,通过增加药物溶解度和渗透性、延长药物作用时间以及减少酶降解来提高药物生物利用度。各个研究小组已经报道了SLNs和NLCs鼻脑给药系统的体内药代动力学和药效学。本综述旨在概述这些研究,并重点介绍针对基于SLN和NLC的制剂开展的研究,这些研究旨在改善中枢神经系统疾病(如神经退行性疾病、癫痫和精神分裂症)的治疗。我们基于这些制剂的药代动力学参数和毒性,讨论了它们的疗效和脑靶向效率,指出了当前知识中的一些空白,并提出了未来的发展目标。