超临界 CO2微乳法制备盐酸小檗碱脂质体工艺的考察与优化

目的：采用 Box Behnken 响应面法优化超临界二氧化碳（CO2）微乳法制备盐酸小檗碱脂质体的工艺。方法考察压力、温度、孵化时间等制备条件对包封率的影响,并采用 Box Behnken 法,以压力、温度和时间为自变量,以包封率为响应优化制备工艺条件,并初步考察了脂质体的粒径。结果Box Behnken 设计优化超临界制备盐酸小檗碱脂质体的最佳工艺条件为：压力19．59 MPa,温度52．78℃,孵化时间1．81 h,预测最佳包封率为59．29％,在该条件下进行验证试验,得到最佳包封率为59．35％,平均包封率为59．26％,实验值与预测值吻合。测得盐酸小檗碱脂质体的平均粒径1．304μm,粒径分布0．3～3μm。结论通过对超临界 CO2微乳法制备盐酸小檗碱脂质体工艺的考察,确定了最佳工艺条件,工艺简单,为脂质体工业化生产提供了可能。     

依托泊苷长循环脂质体工艺处方设计与优化的研究

目的优化依托泊苷长循环脂质体的制备处方及工艺。方法以两亲性聚乙二醇一二硬脂酰磷脂乙醇胺为修饰体，采用薄膜超声．挤压法制备空白长循环脂质体；铵离子梯度法包封依托泊苷，制备依托泊苷长循环脂质体。以包封率为考察指标，采用正交设计法优化依托泊苷长循环脂质体的制备处方及工艺。结果优化后的依托泊苷长循环脂质体的工艺和处方：药脂比例为1：5tool·mol^-1、胆固醇与磷脂比例为0．3：1（W／w）、硫酸铵离子浓度为200mmol·L%^-1、包封温度为55℃。长循环脂质体平均粒径均小于1μm，药物平均包封率86．45％。结论该方法包封率高、粒径小且分布较窄，简便易行。     

运用Box—Behnken设计-效应面法对尼莫地平纳米乳剂处方工艺的优化

目的：运用Box—Behnken设计-效应面法优化尼莫地平纳米乳剂的处方工艺。方法：采用微射流法制备尼莫地平纳米乳剂,分别以聚氧乙烯蓖麻油（CremophorEL）的用量（X1）、大豆卵磷脂（SPC）的用量（X2）和中链脂肪酸甘油三酯（MCT）的用量（X3）为考察对象,以平均粒径（MD）（Y1）、粒径分布（CV）（Y2）为评价指标,运用三因素三水平Box．Behnken设计．效应面法筛选尼莫地平纳米乳剂的最佳处方工艺。结果：尼莫地平纳米乳剂的最优处方用量为X1=3．68％,X2=2．96％,X3=8．6％;按此处方用量制得的尼莫地平纳米乳剂,其平均粒径为（63．3±3．4）nm,粒径分布为（O．26±0．03）％。结论：运用Box—Behnken设计-效应面法优化尼莫地平纳米乳剂的处方工艺是可行的。     

Box-Behnken效应面法优化制备主动载药盐酸小檗碱脂质体

目的采用Box-Behnken效应面法筛选最佳处方,制备盐酸小檗碱脂质体。方法采用薄膜分散-p H梯度法制备脂质体,分别以磷脂与胆固醇质量比、脂药质量比、外水相p H值、孵化温度为考察对象,以包封率、粒径和载药量为评价指标,采用4因素3水平Box-Behnken效应面设计法筛选盐酸小檗碱脂质体的最佳处方。采用阳离子交换树脂微柱离心法测定包封率,动态激光散射法测定脂质体的粒径,并采用透射电镜观察制得的脂质体形态。结果最优处方工艺条件为磷脂与胆固醇质量比为3.38∶1,脂药质量比为22∶1,外水相p H为6.88,孵化温度为59℃。以最优处方制备的盐酸小檗碱脂质体平均粒径、包封率、载药量与预测值偏差较小。结论采用Box-Behnken效应面法优化盐酸小檗碱脂质体工艺处方是可行的。     

Box-Behnken效应面法优化丁香挥发油脂质体处方

目的:采用Box-Behnken效应面法优化丁香挥发油脂质体处方。方法:乙醇注入法制备丁香挥发油脂质体,以磷脂与丁香挥发油质量比(X1)、磷脂与胆固醇质量比(X2)、磷脂浓度(X3)为研究对象,包封率为评价指标,通过Box-Behnken效应面法筛选丁香挥发油脂质体最佳处方。结果:X_1=5,X_2=3.9,X_3=11.72mg/mL;丁香挥发油脂质体包封率为(73.74±2.27)%,与预测值偏差为0.81%;载药量为(12.79±0.43)%,粒径为(73.67±3.58)nm,PDI为0.221±0.024,Zeta电位为(-24.3±6.8)mV。结论:BoxBehnken效应面法可以简单有效的运用于丁香挥发油脂质体的处方优化。优化得到的脂质体处方合理,包封率较高,理化性质考察合格。     

Box-Behnken效应面法优化长春西汀长循环脂质体处方

目的通过优化手段筛选最佳处方,制备长春西汀长循环脂质体。方法采用薄膜分散法制备长循环脂质体,分别以磷脂质量浓度(1ρ)、Tween80质量浓度(ρ2)、磷脂-药质量比(ms∶md)为考察对象,以包封率(Y1)、载药量(Y2)和粒径(d)为评价指标,利用三因素三水平Box-Behnken效应面设计法筛选长循环脂质体的最佳处方;透射电子显微镜考察其形态与粒径。结果长循环脂质体的包封率为85.9%;载药量18.5 mg.g-1;粒径为213.4 nm,与理论值偏差均小于10%。结论长春西汀长循环脂质体采用Box-Behnken实验设计法优化是可行的。     

去氢骆驼蓬碱脂质体的制备和体外释放特性

目的：研究去氢骆驼蓬碱（harmine,HM）脂质体的制备工艺和体外释放特性。方法：运用薄膜分散-pH值梯度法制备HM．脂质体以及高速离心法分离脂质体与游离药物,并测定其包封率;借助综合评分法,评价其粒径、多分散系数、包封率、载药量指标;运用正交优化实验法考察磷脂-胆固醇与药-脂比、超声时间、外相pH值对脂质体的影响,述选最优工艺处方,评价脂质体与原料药的体外释放情况。结果：最优处方因素为磷脂-胆固醇比值为4：1,超声时间为300S,药-脂比值为1：5,外相pH值为6,8,即X13X23X32X43,经实验验证其粒径为（155.0±14．5）nm,多分散系数为（0．148±0．011）,包封率为（80．90±0．01）％,载药量为（11．16±0．01）％;其原料药0．5h累积释放百分比大于50％,不到2h已全部释放,而优化后的脂质体在1h内其累积释放百分比大于50％,4h后释放完成。结论：采用薄膜分散-pH值梯度法,以最优处方制得HM-脂质体,其粒径大小适中、形态均匀,包封率和载药量相对较高,体外释放显示具有较好的缓释特性。     

环孢素A脂质体制备及其体外释药方法学考察

目的：考察环孢素A（cyclosporinA,csA）脂质体的制备方法、理化性质及其体外释放行为。方法：比较薄膜分散法、逆向蒸发法、乙醇注入法、乙醚注入法所得的环孢素A脂质体（CsA—Lip）,并以包封率和载药量为综合指标,正交设计优化CsA—Lip处方工艺;分别采用动态透析法和超速离心法研究CsA—Lip的体外释放行为。结果：乙醇注入法制备CsA—Lip的平均粒径为（80．41±3．12）nm,包封率为（87．09±0．03）％,载药量为（4．98±0.45）％,24h释放44％。结论：经优化制备的CsA脂质体具有较高的包封率和载药量,并具有缓释作用。     

星点设计-效应面法优化平阳霉素脂质体的处方及工艺

目的：优化载平阳霉素脂质体的处方及其制备工艺。方法：以其包封率为考察指标,以平阳霉素与所用脂质的比、所用磷脂与胆固醇的比、制备温度为考察项,采用星点设计-效应面法优化盐酸平阳霉素脂质体的处方及工艺。结果：确定其最优处方为平阳霉素与脂质的比为0.15（W/W）,所用磷脂与胆固醇的比为4.5（W/W）,制备温度为42.3℃,实测值与预测值的最终差异显示无统计学意义。该脂质体的平均粒径为136 nm,Zeta电位为（-28.55±6.81）mV。结论：所选制备工艺较为合理,星点设计-效应面法可用于该制剂的处方优化。     

姜黄素-汉防己碱共递送抗病毒复方脂质体的构建

目的：制备寡聚透明质酸衍生物 oHA 修饰的姜黄素－汉防己碱中药抗病毒脂质体,并对其进行体外释放和稳定性研究。方法用薄膜分散法制备了寡聚透明质酸衍生物修饰的姜黄素－汉防己碱脂质体,以粒径和包封率作为两个重要的参考指标,使用粒度仪测定了粒径,使用紫外分光光度法测定包封率。结果用 Box －Be-hnken 效应面优化法确定了最佳磷脂胆固醇比为2．5∶1,最佳姜黄素－汉防己碱比例为2．8∶1,寡聚透明质酸衍生物的用量为1．80％,通过最佳处方制备的脂质体的粒径是201．06 nm,包封率是70．94％。结论制备的脂质体具有良好的稳定性,均匀的粒径分布,证明了脂质体具有良好的体外释放活性,良好的稳定性,为进一步研究抗病毒联合机制奠定基础。     

Box-Behnken效应面法优化姜黄素纳米结构脂质载体处方

目的采用Box-Behnken效应面法优化处方,制备姜黄素纳米结构脂质载体,并考察其理化性质。方法采用薄膜超声法制备载药纳米结构脂质载体,分别以药物质量浓度(X1)、总脂质质量浓度(X2)和混合乳化剂质量浓度(X3)为考察对象,以包封率(Y1)、粒径(Y2)为评价指标,利用三因素三水平Box-Behnken效应面设计法筛选载药纳米结构脂质载体的最佳处方。采用微柱离心法测定制剂的包封率,透射电镜观察其外观形态,动态光衍射法测定其粒径及Zeta,差示扫描量热法确证姜黄素在载体中的分散状态。结果最优处方制备的载药纳米结构脂质载体外形呈圆形或椭球形,粒径分布均匀,平均粒径为(58.37±2.60)nm,Zeta电位为-(22.6±0.88)mV,包封率为(93.48±0.86)%,DSC结果表明药物以非结晶状分散于纳米结构脂质载体中。结论采用Box-Behnken效应面法优化姜黄素纳米结构脂质载体处方是可行的。     

Nano-transfersomes as a novel carrier for transdermal delivery

The aim of this study was to design and optimize a nano-transfersomes of Diclofenac diethylamine (DDEA) and Curcumin (CRM). A 3³ factorial design (Box–Behnken) was used to derive a polynomial equation (second order) to construct 2-D (contour) and 3-D (Response Surface) plots for prediction of responses. The ratio of lipid to surfactant (X₁), weight of lipid to surfactant (X₂) and sonication time (X₃) (independent variables) and dependent variables [entrapment efficiency of DDEA (Y₁), entrapment efficiency of CRM (Y₂), effect on particle size (Y₃), flux of DDEA (Y₄), and flux of CRM (Y₅)] were studied. The 2-D and 3-D plots were drawn and a statistical validity of the polynomials was established to find the compositions of optimized formulation. The design established the role of the derived polynomial equation, 2-D and 3-D plots in predicting the values of dependent variables for the preparation and optimization of nano-transfersomes for transdermal drug release.     

Development of novel sustained release matrix pellets of betahistine dihydrochloride: effect of lipophilic surfactants and co-surfactants

Sustained release matrix pellets of the freely water soluble drug, betahistine dihydrochloride (BH), were prepared using freeze pelletization technique. Different waxes and lipids (cetyl alcohol, beeswax, glyceryl tripalmitate (GTP) and glyceryl tristearate) were evaluated for the preparation of matrix pellets. A D-optimal design was employed for the optimization and to explore the effect of drug loading (X₁), concentration of lipophilic surfactant (X₂), concentration of co-surfactant (X₃) and wax type (X₄) on the release extent of the drug from matrix pellets. The entrapment efficiency (Y₁), pellet diameter (Y₂), and the percentage drug released at given times were selected as dependent variables. Results revealed a significant impact of all independent variables on drug release from the formulated pellets. The lipophilic surfactant significantly increased both the entrapment efficiency and the in vitro drug release and significantly decreased the pellet size. The optimized BH-loaded pellets were composed of 19.95% drug loading, 9.95% Span^® 80 (surfactant), 0.25% Capmul^® (co-surfactant) using glyceryl tripalmitate as a matrix former. The release profiles of the drug from hard gelatin capsule containing optimized pellets equivalent to 32?mg BH was similar to that of target release model for once-daily administration based on similarity factor. It could be concluded that a promising once-daily capsule containing sustained release pellets of BH was successfully designed.     

洛莫司汀-碘海醇复方脂质体的制备及包封率测定

目的:制备洛莫司汀-碘海醇复方脂质体,并考察其质量、测定其包封率。方法:以逆相蒸发法制备复方脂质体;以磷脂种类(A)、磷脂与胆固醇质量比(B)、脂质质量浓度(C)为因素,以两主药的包封率为评价指标,采用正交设计法优化处方;以两主药的包封率及脂质体的粒径和Zeta电位为指标进行验证试验。结果:优化处方结果显示,A为大豆磷脂80,B为2∶1,C为33mg/ml。验证试验结果显示,洛莫司汀包封率约为75.7%,碘海醇包封率约为65.7%;脂质体粒径约为236.5 nm,Zeta电位约为-42.2mV。结论:采用该处方与工艺可成功制备包封率较高的洛莫司汀-碘海醇复方脂质体,质量符合要求。     

饱和磷脂脂质体的室温下制备及其性质的研究

目的考察室温下用饱和磷脂制备脂质体的新方法(加入特殊的附加剂)及其对以蛋白多肽类为主药的包封情况,并研究了脂质体的体外性质。方法通过加入特殊的附加剂,用反相蒸发-超声分散法制备脂质体,并初步考察了其室温放置的稳定性;以尿激酶为例,考察所得脂质体的粒度分布和形态;对不同的蛋白多肽类药物进行包封;以阿霉素为模型药物,考察脂质体在PBS和小牛血清中的泄漏。结果附加剂DSPE-PEG 2000只需1%的用量(占磷脂的摩尔比),即可用饱和磷脂在室温下超声1 min制得脂质体;所得脂质体平均粒径在100 nm以下,形态圆整,室温放置稳定;对胰岛素和水蛭素的包封率与普通脂质体相近(23%),对尿激酶包封率高达(65.4±2.6)%;体外泄漏缓慢。结论提出的制备方法条件温和,产品稳定性好,非常适合高分子量蛋白类药物,并可获得较高的包封率,是一种很有前景的脂质体制备方法。     

Box-Behnken效应面法优化姜黄素正负离子固体脂质纳米粒的处方

目的 采用Box-Behnken效应面法筛选姜黄素正负离子固体脂质纳米粒的最优处方.方法 采用乳化蒸发-低温固化法制备姜黄素的固体脂质纳米粒,以固体脂质的质量、卵磷脂的质量和混合表面活性剂为考察对象,以包封率和脂质载药量为考察指标,利用3因素3水平Box-Behnken效应面设计法筛选姜黄素固体脂质纳米粒的最优处方.结果 按最优处方制备固体脂质纳米粒的包封率为94.20％ ±2.55％、脂质载药量为3.49％±0.11％,平均粒径为194.9 ±12.0 nm,Zeta电位为-28.15 ±2.72 mV.结论 采用Box-Behnken效应面法优化姜黄素正负固体脂质纳米粒的处方是有效、可行的.     

Maximizing the Therapeutic Efficacy of Imatinib Mesylate–Loaded Niosomes on Human Colon Adenocarcinoma Using Box-Behnken Design

This research purposed to formulate an optimized imatinib mesylate (IM)–loaded niosomes to improve its chemotherapeutic efficacy. The influence of 3 formulation factors on niosomal vesicular size (Y₁), zeta potential (Y₂), entrapment capacity percentage (Y₃), the percentage of initial drug release after 2 h (Y₄), and the percentage of cumulative drug release after 24 h (Y₅) were studied and optimized using Box-Behnken design. Optimum desirability was specified and the optimized formula was prepared, stability tested, morphologically examined, checked for vesicular bilayer formation and evaluated for its in vitro cytotoxicity on 3 different cancer cell lines namely MCF-7, HCT-116, and HepG-2 in addition to 1 normal cell line to ensure its selectivity against cancer cells. The actual responses of the optimized IM formulation were 425.36 nm, ?62.4 mV, 82.96%, 18.93%, and 89.45% for Y₁, Y₂, Y₃, Y₄, and Y₅, respectively. The optimized IM-loaded niosomes confirmed the spherical vesicular shape imaged by both light and electron microscopes and further proven by differential scanning calorimetry. Moreover, the optimized formula exhibited improved stability on storage at 4 ± 2°C and superior efficacy on MCF7, HCT-116, and HepG2 as IC₅₀ values were 6.7, 16.4, and 7.3 folds less than those of free drug, respectively. Interestingly, IC₅₀ of the optimized formula against normal cell line was ranged from 3 to 11 folds higher than in different cancer cells indicating a higher selectivity of the optimized formula to cancer cells. In conclusion, the incorporation of IM in niosomes enhanced its efficacy and selectivity toward cancer cells, presenting a promising tool to fight cancer using this approach.     

枸橼酸二甲双胍阿霉素脂质体的制备

目的制备二甲双胍阿霉素脂质体并对其制备工艺进行优化。方法以二甲双胍阿霉素脂质体的包封率为评价指标,对其处方和制备工艺进行筛选和优化。分别考察了磷脂与胆固醇的比例、水化介质中阴离子的种类、水化介质的浓度、水化介质的pH值、载药温度、载药时间对二甲双胍阿霉素脂质体包封率的影响。结果最终优化的处方为m(hydrogenated soybean phosphatidylcho-line,HSPC)∶m(cholesterol,CH)∶m(polyethylene glycol 2000-cholesteryl hemisuccinate,mPEG2000-CHEMS)=3.0∶1.0∶1.0,以pH为7.00的300 mmol.L-1的枸橼酸二甲双胍为水化介质,60℃载药60 min,所制备的脂质体包封率可达98.7%。结论以枸橼酸二甲双胍离子梯度法制备的阿霉素脂质体包封率高,方法可行。     

Optimization of controlled release nanoparticle formulation of verapamil hydrochloride using artificial neural networks with genetic algorithm and response surface methodology

This study was performed to optimize the formulation of polymer–lipid hybrid nanoparticles (PLN) for the delivery of an ionic water-soluble drug, verapamil hydrochloride (VRP) and to investigate the roles of formulation factors. Modeling and optimization were conducted based on a spherical central composite design. Three formulation factors, i.e., weight ratio of drug to lipid (X₁), and concentrations of Tween 80 (X₂) and Pluronic F68 (X₃), were chosen as independent variables. Drug loading efficiency (Y₁) and mean particle size (Y₂) of PLN were selected as dependent variables. The predictive performance of artificial neural networks (ANN) and the response surface methodology (RSM) were compared. As ANN was found to exhibit better recognition and generalization capability over RSM, multi-objective optimization of PLN was then conducted based upon the validated ANN models and continuous genetic algorithms (GA). The optimal PLN possess a high drug loading efficiency (92.4%, w/w) and a small mean particle size (∼100 nm). The predicted response variables matched well with the observed results. The three formulation factors exhibited different effects on the properties of PLN. ANN in coordination with continuous GA represent an effective and efficient approach to optimize the PLN formulation of VRP with desired properties.