Artificial neural network for optimizing the formulation of curcumin-loaded liposomes from statistically designed experiments.

IF 4.4 3区 医学 Q2 ENGINEERING, BIOMEDICAL
Progress in Biomaterials Pub Date : 2022-03-01 Epub Date: 2022-01-18 DOI:10.1007/s40204-022-00179-6
Ibilola M Cardoso-Daodu, Margaret O Ilomuanya, Andrew N Amenaghawon, Chukwuemeka P Azubuike
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引用次数: 5

Abstract

Curcumin is a primary polyphenol of the rhizomatous perennial plant called Curcuma Longa. Curcumin interferes favorably with the cellular events that take place in the inflammatory and proliferative stages of wound healing, hence its importance in skin regeneration and wound healing. Curcumin is however lipophilic, and this must be considered in the choice of its drug delivery system. Liposomes are spherical vesicles with bi-lipid layers. Liposomes can encapsulate both lipophilic and hydrophilic drugs, hence their suitability as an ideal drug delivery system for curcumin. There is, nevertheless, a tendency for liposomes to be unstable and have low encapsulation efficiency if it is not formulated properly. Formulation optimization of curcumin-loaded liposomes was studied by the application of artificial neural network (ANN) to improve encapsulation efficiency and flux of the liposomes. The input factors selected for optimization of the formulation were sonication time, hydration volume, and lipid/curcumin ratio. The response variables were encapsulation efficiency and flux. The maximum encapsulation efficiency and flux were obtained using lipid/curcumin ratio of 4.35, sonicator time of 15 min, and hydration volume of 25 mL. The maximum encapsulation efficiency and flux predicted were 100% and 51.23 µg/cm2/h, respectively. The experimental values were 99.934% and 51.229 µg/cm2/h, respectively. Curcumin-loaded liposome formulation is a promising drug delivery system in the pharmaceutical industry when formulated using optimized parameters derived from ANN statistically designed models.

Abstract Image

Abstract Image

从统计设计的实验中优化姜黄素脂质体配方的人工神经网络。
姜黄素是一种多年生根茎植物姜黄的主要多酚。姜黄素有利地干扰发生在伤口愈合的炎症和增殖阶段的细胞事件,因此它在皮肤再生和伤口愈合中的重要性。然而,姜黄素是亲脂性的,在选择给药系统时必须考虑到这一点。脂质体是具有双脂层的球形囊泡。脂质体可以包裹亲脂性和亲水性药物,因此它们是姜黄素的理想药物递送系统。然而,如果不适当配制,脂质体有不稳定和低包封效率的趋势。为了提高姜黄素脂质体的包封效率和通量,应用人工神经网络(ANN)对其配方进行优化研究。以超声时间、水化体积、脂质/姜黄素比为优化因素。响应变量为包封效率和通量。在脂质/姜黄素比为4.35、超声时间为15 min、水化体积为25 mL的条件下,获得最大包封效率和包封通量,最大包封效率和包封通量分别为100%和51.23µg/cm2/h。实验值分别为99.934%和51.229µg/cm2/h。姜黄素负载脂质体制剂是一种很有前途的药物输送系统,在制药工业中,当配方使用优化参数得到的ANN统计设计模型。
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来源期刊
Progress in Biomaterials
Progress in Biomaterials MATERIALS SCIENCE, BIOMATERIALS-
CiteScore
9.60
自引率
4.10%
发文量
35
期刊介绍: Progress in Biomaterials is a multidisciplinary, English-language publication of original contributions and reviews concerning studies of the preparation, performance and evaluation of biomaterials; the chemical, physical, biological and mechanical behavior of materials both in vitro and in vivo in areas such as tissue engineering and regenerative medicine, drug delivery and implants where biomaterials play a significant role. Including all areas of: design; preparation; performance and evaluation of nano- and biomaterials in tissue engineering; drug delivery systems; regenerative medicine; implantable medical devices; interaction of cells/stem cells on biomaterials and related applications.
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