CN115645386A - Preparation method for optimizing colchicine alcohol transfersome based on response surface method combined with entropy weight method - Google Patents
Preparation method for optimizing colchicine alcohol transfersome based on response surface method combined with entropy weight method Download PDFInfo
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Abstract
The invention discloses a preparation method for optimizing a colchicine alcohol transfersome based on a response surface method combined with an entropy weight method, which takes soybean lecithin, sodium deoxycholate and ethanol as investigation factors and takes particle size, PDI (PDI), potential and encapsulation rate as investigation indexes; experiment design is carried out based on a Box-Behnken response surface, an entropy weight method is adopted to assign weights to 4 indexes, and comprehensive scoring is used as an evaluation index to optimize the preparation process of the colchicine alcohol transfersome. The method has the advantages of more reasonable and reliable result, smaller deviation between the measured value and the predicted value and good correlation. The prepared colchicine alcohol transfersome has uniform size, uniform distribution, stable potential and higher entrapment rate than colchicine liposome with active drug loading, and meets the requirement of transdermal drug delivery.
Description
Technical Field
The invention belongs to the technical field of preparation of alcohol transfersomes, and particularly relates to a preparation method for optimizing a colchicine alcohol transfersome based on a response surface method and an entropy weight method.
Background
Colchicine (COL) is an alkaloid that has been used for many years to treat acute gout, but has a broad first-pass metabolism, a low therapeutic index, and poor oral bioavailability (25% -50%). In addition, oral colchicine administration can exhibit mild to severe gastrointestinal side effects including abdominal cramps and pain, nausea, vomiting, and diarrhea. These side effects are common in 80% of patients even at therapeutic doses.
Aims at solving the problems of dose-dependent side effect and poor bioavailability of the oral colchicine. At present, studies report that colchicine is prepared into liposome, but colchicine can be dissolved in water or ethanol, and the entrapment rate of colchicine in lipid carrier is not high due to the solubility of colchicine.
Alcohol Transfersomes (TEs) have the advantages of two carriers, namely ethosomes and transfersomes, in the aspect of transdermal administration, and can entrap hydrophilic or hydrophobic drugs, and many researches prove that the TEs can enhance the transdermal administration effect of drugs with different physicochemical properties. Therefore, the preparation of colchicine into alcohol transfersomes is one direction of research, and no literature report on the preparation of colchicine into alcohol transfersomes is found at present.
At present, the Box-Behnken response surface design method is mostly used for optimizing the traditional Chinese medicine extraction process and the extract drying process. When a plurality of indexes are inspected by adopting BBD, the individual indexes are generally required to be analyzed one by one, only a large number of repeated experiments can be performed, or different indexes are artificially and subjectively empowered, so that the intervention of subjective factors cannot be avoided. In some researches, screening is performed by assigning weights to two indexes by a subjective weighting method to obtain a comprehensive score, but when the number of investigation indexes exceeds two, other important indexes are often screened out for the weighting mode, so the weighting mode is not attractive.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention aims to provide a method for optimizing a colchicine alcohol transfersome based on a response surface method and an entropy weight method, the method has more reasonable and reliable result, the deviation between the measured value and the predicted value is smaller, and the prepared colchicine alcohol transfersome has uniform size, uniform distribution, stable potential and excellent encapsulation efficiency.
The invention is realized by the following technical scheme:
a method for optimizing a colchicine alcohol carrier based on a response surface method combined with an entropy weight method comprises the following steps:
(1) Dissolving soybean lecithin and a surfactant in ethanol to form a blank carrier; dissolving colchicine in water to form water phase, injecting the water phase into blank transfersome, stirring at constant temperature to obtain colchicine alcohol transfersome;
(2) Selecting the dosage of lecithin, the dosage of a surfactant and the volume of ethanol as investigation factors by adopting a single-factor experiment;
(3) Carrying out factor level experiment design based on Box-Behnken response surface by taking the particle size, PDI, zeta potential and encapsulation rate as indexes;
(4) Calculating the entropy value and the weight coefficient of each index by an objective entropy weight method;
(5) Performing quadratic multiple regression fitting analysis on the data by using Design-Expert software to obtain a model equation between the lecithin using amount, the surfactant using amount, the ethanol volume and the comprehensive score, and performing variance analysis by using a comprehensive score value model;
(6) And solving according to a model equation to obtain the optimal preparation condition of the colchicine alcohol transfersome.
Preferably, in step (1), the surfactant is tween 20 or sodium deoxycholate, preferably sodium deoxycholate.
Preferably, in the step (1), the stirring temperature at constant temperature is 40-60 ℃, the rotation speed is 600-2000 rpm, and the stirring time is 30-120 min.
Preferably, in the step (4), the step of calculating the entropy value and the weight coefficient of each index by the objective entropy weight method is as follows:
(a) Index normalization processing: setting an original data matrix of m evaluation indexes and n evaluation objects as X = (aij) mn, normalizing the original data matrix to obtain X' = (xij) mn, and normalizing the positive indexes by the following formula;
x 'ij = (aij-min j { aij })/(max j { aij } -min j { aij }), wherein X' ij represents the value of the j-th evaluation index in the ith test, and i =1,2,3, \ 8230;, m; j =1,2,3, \8230;, n;
(b) Converting the original data array (aij) mn into a probability matrix (Pij) mn; pi in the information entropy formula is the probability of certain information, and satisfies 0 ≤ Pi ≤ 1, so the matrix (aij) mn must be normalized, and the processed matrix can be used as the probability matrix of the evaluation index. Wherein Pij represents the probability of the j test under the ith evaluation index;
(c) And calculating the entropy value of the index, and determining the information entropy (Hi) of the ith evaluation index.
(d) An entropy weight coefficient (Wj) of the index is calculated.
Preferably, in the step (5), the model equation between the lecithin dosage, the surfactant dosage, the ethanol volume and the comprehensive score is obtained as follows: y =0.0416106+0.0105741A +0.00718237B +0.0108031C-0.00383408AB +0.0122264AC +0.00610334A 2 +0.00390619B 2 +0.0265679C 2 Using the comprehensive score value model to perform variance analysis and determine the coefficient r by an equation 2 ＝0.7801。
Preferably, in step (6), the best preparation conditions for the colchicine alcohol transfersome are 500mg of lecithin, 50mg of sodium deoxycholate and 4mL of ethanol.
Compared with the prior art, the invention has the following beneficial effects:
the invention takes soybean lecithin, sodium deoxycholate and ethanol as investigation factors, and takes particle size, PDI, potential and encapsulation rate as investigation indexes; experiment design is carried out based on a Box-Behnken response surface, an entropy weight method is adopted to assign weights to 4 indexes, and comprehensive scoring is used as an evaluation index to optimize the preparation process of the colchicine alcohol transfersome. In order to avoid the influence of human factors, the weight of the evaluation index is obtained by using an objective entropy weight method, the method can judge the importance degree of the index according to the value variation degree of the entropy weight coefficient of each index, and the result is more reasonable and reliable. The process conditions are optimized according to the fitting equation, so that the deviation between the measured value and the predicted value of the prepared colchicine alcohol transfersome is small, and the correlation is good.
The invention optimizes the preparation process of the colchicine alcohol transfersome by using a Box-Behnken response surface design method and combining an entropy weight method, and the colchicine alcohol transfersome prepared by the method has uniform size, uniform distribution, stable potential and higher entrapment rate than the colchicine liposome with active drug loading, thereby meeting the requirements of transdermal drug delivery alcohol transfersome.
Drawings
FIG. 1 is a plot of contour plots and response surfaces of the effect of different factors on the composite score values;
FIG. 2 is a particle size distribution diagram of COL-TES;
FIG. 3 is a zeta potential diagram for COL-TES;
FIG. 4 is a transmission electron micrograph of COL-TES.
Detailed Description
The present invention is further illustrated by the following specific embodiments, which are not intended to limit the scope of the invention.
Example 1:
1 Instrument and reagent
1.1 Instrument
High performance liquid chromatography (THERMO V3000, siemer femier technologies); high speed centrifuges (model BT-25S, manufactured by Wauter, inc., changzhou city); one in ten-thousandth electronic analytical balance (model AB135-S, sydows scientific instruments (beijing) ltd); a heat collection type constant temperature heating magnetic stirrer (DF-101S, provisions of City Instrument manufacturing, ltd.); laser particle sizers (model 3000HS, malvern, uk); transmission electron microscopy (JEM-2100 type, EILL, japan); ultrasonic cell disruptors (SFX model, emerson, USA).
1.2 drugs and reagents
Colchicine COL (98% purity, batch No. 101176-201001, sichuan Biotech Co., ltd.); soya lecithin (purity > 98%, batch No. K1915226, shanghai alatin biochem technologies ltd); sodium deoxycholate (98% pure, lot No. C11584234, shanghai mclin biochem technologies, ltd); ethanol (chromatographically pure, shanghai Allatin Biotechnology GmbH); methanol (chromatographically pure Fisher corporation); ultrapure water.
1.3 screening of surfactants
The influence of the surfactant on the preparation is inspected by utilizing a single factor, the surfactant is span 20, tween 20 and sodium deoxycholate which are respectively 30mg, other components (soybean lecithin 200mg and ethanol 2 mL) are kept consistent, the influence of the surfactant on the particle size, PDI and zeta potential is inspected, and the formula of the COL alcohol transfersome is optimized.
TABLE 1
From the above results, the importance of the four indices is the particle diameter > PDI > zeta potential. The particle size of the alcohol carrier added with the sodium deoxycholate is the smallest, and the difference is obvious; PDI of the three components is less than 0.2, and the requirements are met; the zeta potential is similar among the three. Comprehensively considering, the surfactant is sodium deoxycholate to carry out subsequent experiments.
2 methods and results
2.1 colchicine assay
2.1.1 chromatographic conditions
A Unitaryl C18 column (4.6 mm. Times.250mm, 5 μm); mobile phase: methanol-water (60; column temperature: 30 ℃; detection wavelength: 254nm; flow rate: 1.0mL/min; sample injection amount: 10 μ L.
2.1.2 Standard Curve
COL control 5mg was weighed accurately into a 10mL measuring flask and a COL control stock solution (500. Mu.g/mL) was prepared with methanol. Methanol was added sequentially to dilute a series of COL control solutions to concentrations of 1.00,2.00,5.00, 10.00, 20.00, 50.00, 100.0, 200.0, 500.0 μ g/mL. Linear regression was performed on the peak area (y) with concentration (x) with the linear equation y =0.6016x-0.1159 (r 2= 0.9997). The results show that the peak area and concentration are in a good linear relationship in the concentration range of 1-500. Mu.g/mL. The RSD of the intra-day precision is 0.29 percent, the RSD of the inter-day precision is 0.08 percent, the average recovery rate is 98.87 percent +/-0.11 percent, and the content determination requirement is met.
2.2 Preparation of COL-TES
Precisely weighing soybean lecithin and sodium deoxycholate in 4mL of ethanol, mixing, placing in a conical flask, and heating for dissolving. Adding 10mg COL into 6mL water to form water phase, slowly injecting the water phase containing COL into conical flask with syringe, maintaining the temperature at 50 deg.C, stirring at 1300rpm for 30min, performing ultrasonic treatment with probe (ultrasonic treatment for 5s, stopping for 5s, amplitude 25%,5 min), and filtering with 0.22 μm filter membrane to obtain the final product.
2.3 encapsulation efficiency determination
2.3.1 Process recovery
Accurately preparing COL solutions with low, medium and high concentrations (0.1, 0.5, 1 mg/ml), centrifuging in ultrafiltration tube (4000 r/min,30 min), collecting continuous filtrate, analyzing the sample injection of the medicinal solution before and after ultrafiltration, and calculating the recovery rate of free medicinal substance. The recovery rate of COL is more than 95%, which meets the requirement (Table 2).
TABLE 2 COL recovery
2.3.2 sample recovery
Accurately adding appropriate amount of COL into blank alcohol transfersome to make COL concentration be 0.1, 0.5 and 1mg/ml respectively, centrifuging (4000 r/min,30 min) in ultrafiltration tube, collecting continuous filtrate, sampling and analyzing drug solution before and after ultrafiltration, and calculating recovery rate. The loading recovery rate of COL is more than 95%, and the loading recovery rate meets the requirement of the method for measuring the encapsulation rate of the alcohol carrier (Table 3).
TABLE 3 recovery of blank alcohol-plus-carrier during ultrafiltration
2.3.3 method for determining encapsulation efficiency
Accurately weighing appropriate amount of COL-TES, placing in an ultrafiltration centrifuge tube, centrifuging (4000 r/min,30 min), taking out outer tube liquid, diluting to constant volume of 10ml with methanol, and determining colchicine content according to 1.2.2.1 chromatographic condition and recording as W1. And (3) taking the same volume of COL-TES methanol to reach a constant volume of 10ml, ultrasonically demulsifying, and determining the colchicine content according to a chromatographic condition of 1.2.2.1 and recording as W2. The encapsulation efficiency was calculated according to equation (1).
Encapsulation ratio = (W2-W1)/W2 (1)
2.4.1 particle size, PDI and zeta potential measurements
And (4) transferring a proper amount of COL-TEs into a sample cell, and detecting the particle size, PDI and zeta potential of the COL-TEs by using a laser particle size analyzer.
2.4.2 Single factor experiment
In order to examine main influence factors of COL-TES prescriptions, the experiment takes the particle size, PDI, potential and encapsulation rate of COL-TES as examination indexes, examines the influence of temperature, rotating speed, stirring time, ethanol dosage, lecithin dosage, sodium deoxycholate dosage and the like on the indexes, and optimizes the COL-TES prescriptions.
TABLE 4 Single factor test factor levels
TABLE 5 Single factor survey arrangement and results
In conclusion, the dosage of lecithin, sodium deoxycholate and ethanol has a significant influence on the prescription. Single factor investigation results verify the significant effects of lecithin, sodium deoxycholate and ethanol on alcohol transporter prescriptions in the literature. Therefore, the main influencing factors are the dosages of lecithin, sodium deoxycholate and ethanol. As can be seen from tables 4 and 5, the optimum temperature was 50 deg.C, the rotation speed was 1300rpm, and the stirring time was 30min. Lecithin has larger difference in 50-500mg, so three levels of 50mg, 275mg and 500mg are selected for response surface optimization design; sodium deoxycholate has great difference in 5-50mg, so three levels of 5mg, 27.5mg and 50mg are selected for response surface optimization design; the ethanol has larger difference within 2-4ml, so three levels of 2ml, 3ml and 4ml are selected for response surface optimization design.
2.5 response surface method Process optimization
2.5.1 determination of factor level Table
According to the pre-experimental results, the temperature is determined to be 50 ℃, the rotating speed is 1300rpm, and the stirring time is 30min. And selecting factors which have larger influence on the experiment to perform BBD optimization. The COL-TES prescription is optimized by BBD with lecithin dosage (A), sodium deoxycholate dosage (B) and ethanol volume (C) as investigation factors and particle size, PDI, zeta potential and encapsulation rate as indexes, and the factor levels are shown in Table 6.
TABLE 6 factor and level design
2.5.2 analysis of data by entropy method
In the information theory, the measurement uncertainty is represented by entropy. In order to eliminate the influence of human factors, an objective entropy weight method is adopted when determining the evaluation index weight. By applying an entropy weight method, each evaluation index is regarded as a random variable, an entropy weight coefficient of the index is calculated, the larger the value variation degree is, the more disorder is, the more information is provided, and the more important the index is; and vice versa. Therefore, the entropy weight method is a more objective weighting method. The calculation steps for assigning weights by the entropy weight method are as follows:
(1) Index normalization processing: assuming that the raw data matrix of the m evaluation indexes and the n evaluation objects is X = (aij) mn, X' = (xij) mn is obtained by normalizing the raw data matrix, and the forward index is normalized by the following formula.
X 'ij = (aij-min j { aij })/(max j { aij } -min j { aij }), wherein X' ij represents the value of the j-th evaluation index in the ith test, and i =1,2,3, \ 8230;, m; j =1,2,3, \8230;, n.
(2) Converting the original data matrix (aij) mn into a probability matrix (Pij) mn; pi in the information entropy formula is the probability of certain information, and satisfies 0 ≤ Pi ≤ 1, so the matrix (aij) mn must be normalized, and the processed matrix can be used as the probability matrix of the evaluation index. Where Pij represents the probability of the j-th trial under the i-th evaluation index.
(3) And calculating the entropy value of the index, and determining the information entropy (Hi) of the ith evaluation index.
(4) An entropy weight coefficient (Wj) of the index is calculated.
Through calculation, entropy values and weight coefficients of the indexes are obtained, and are shown in table 7 below.
Table 7 entropy value and weight coefficient of each index
2.5.3 Experimental arrangement
And selecting an optimization method according to the factor level table, and performing optimization experiments according to random arrangement of the experiments. And (3) performing secondary multiple regression fitting analysis on the data by using Design-Expert software to obtain a model equation among lecithin (A), sodium deoxycholate (B), ethanol (C) and comprehensive score (Y). And carrying out variance analysis on the comprehensive grade value model.
The BBD protocol and the results of the composite score are shown in Table 8. Performing second multiple regression fitting analysis on the data in the table 8 by using software to obtain a second multiple regression model equation between lecithin (A), sodium deoxycholate (B), ethanol (C) and the comprehensive score (Y): y =0.0416106+0.0105741A +0.00718237B +0.0108031C-0.00383408AB +0.0122264AC +0.00610334A 2 +0.00390619B 2 +0.0265679C 2 Using the comprehensive score value model to perform variance analysis and determine the coefficient r by an equation 2 ＝0.7801。
TABLE 8 BBD-response surface test design and results
The analysis of variance results (table 9) can be obtained, the P value of the model is less than 0.05, the significance is obvious, the reliability is high, the mismatching item is not significant, the model is proved to have good fitting degree and statistical significance, and target indexes under different conditions can be predicted, so that the model can be used for screening and predicting prescriptions.
TABLE 9 analysis of variance results
Note: the difference is not significant when P is more than 0.05 and the difference is significant when P is less than 0.05
2.5.4 Effect surface optimization
And generating a three-dimensional surface graph and a contour graph of which the comprehensive score values change along with factors by adopting Design-Expert software according to the fitted model. The contour map and the three-dimensional map enable prediction and examination of the relationship between each factor and the composite score. As can be seen from FIG. 1, the contour lines of AB and AC are elliptic, which shows that the interaction between lecithin and sodium deoxycholate and the interaction between lecithin and ethanol are obvious, and shows that the interaction between AB and AC has a large influence on the comprehensive score.
2.5.5 Verification of COL-TES optimal prescriptions
And (4) solving by combining a quadratic regression equation to obtain the optimal prescription of 500mg of lecithin, 50mg of sodium deoxycholate and 4mL of ethanol (the comprehensive score predicted value is 0.115). The process is carried out for three times in parallel, and the index encapsulation efficiency, potential, PDI and particle size are measured.
The predicted optimal prescription is 500mg of lecithin, 50mg of sodium deoxycholate and 4mL of ethanol (the predicted value of the comprehensive score is 0.115). Under this prescription, parallel experiments were performed three times to determine particle size, PDI, potential and encapsulation efficiency, see fig. 2 and 3. The encapsulation efficiencies were found to be 60.99%, 60.6%, 59.12%, respectively; the particle diameters are 151nm, 112.8nm and 116.7nm respectively; the potentials are-14.5 mV, -16mV, -16.9mV respectively; PDIs 0.205, 0.211, 0.262, respectively. The corresponding comprehensive scores are 0.1062, 0.1088 and 0.1074 respectively, and the RSD of the predicted value is 3.39%, so that the process is stable and reliable.
2.5.4 COL-TES morphometric examination
Sucking a proper amount of optimal prescription sample, dripping on a copper net, sucking dry with filter paper along the edge after 10min, then dyeing with 2% phosphotungstic acid, standing for 6min, and observing the shape of COL-TES under the optimal prescription by using a transmission electron microscope after the sample is air-dried (figure 4). As can be seen from FIG. 4, the COL-TES in the optimal prescription are spherical-like, and have no adhesion with each other, uniform distribution and uniform size, which indicates that the prepared optimal prescription has good dispersibility.
Comparative example 1: preparation of colchicine liposome
Accurately weighing 6.0mg COL and 1.0mg sodium deoxycholate, and dissolving in 21mL water to obtain water phase; accurately weighing 60.0mg of egg yolk lecithin and 2.0mg of cholesterol in 3mL of diethyl ether, and heating to dissolve the egg yolk lecithin and the cholesterol to obtain an oil phase; stirring, slowly injecting the oil phase into water phase containing COL and sodium deoxycholate via adherence with injector below liquid level, maintaining constant temperature at 50 deg.C, stirring at 20rpm for 2 hr, ultrasonic treating for 3min, and filtering with 0.22 μm microporous membrane to obtain COL-DLs.
The results are shown in Table 10, which shows that the encapsulation efficiency of colchicine alcohol transfersomes is (60.24 + -0.99)%, and the encapsulation efficiency of colchicine liposomes is (52.90 + -0.65)%. The entrapment rate of the colchicine alcohol transfersome is superior to that of the colchicine liposome for active drug loading.
TABLE 10 encapsulation efficiency of colchicine liposomes
In summary, in order to avoid the influence of human factors, the invention obtains the weight of the evaluation index by using an objective entropy weight method. The method can judge the importance degree of the index according to the value variation degree of the entropy weight coefficient of each index. Through the processing, the weight of the encapsulation efficiency is the largest, the potential is the second order, and the difference between the particle size and the PDI is small, which shows that the variation degree of the result of the encapsulation efficiency obtained through experiments is high and is the most important index of the four indexes, and the particle size and the PDI are not changed greatly along with the change of the investigation factors, so the distributed weight is not high. The test result is always deviated by weighting through personal experience, the weight of each index is calculated by an entropy weight method, and the result is more reasonable and reliable. The process conditions are optimized according to the fitting equation, the deviation between the COL-TES measured value and the predicted value is small, the correlation is good, and reliable data are provided for screening the optimal prescription by combining the BBD and the entropy weight method. The optimized COL-TES has uniform size, uniform distribution, stable potential and encapsulation efficiency superior to that of colchicine liposome for active drug loading, and meets the requirement of transdermal TEs administration.
Claims (6)
1. A preparation method for optimizing a colchicine alcohol carrier based on a response surface method combined with an entropy weight method is characterized by comprising the following steps:
(1) Dissolving soybean lecithin and a surfactant in ethanol to form a blank carrier; dissolving colchicine in water to form a water phase, injecting the water phase into a blank transfersome, and stirring at constant temperature to obtain a colchicine alcohol transfersome;
(2) Selecting the dosage of lecithin, the dosage of a surfactant and the volume of ethanol as investigation factors by adopting a single-factor experiment;
(3) Carrying out factor level experiment design based on Box-Behnken response surface by taking the particle size, PDI, zeta potential and encapsulation rate as indexes;
(4) Calculating the entropy value and the weight coefficient of each index by an objective entropy weight method;
(5) Performing secondary multiple regression fitting analysis on the data by using Design-Expert software to obtain a model equation between the lecithin using amount, the surfactant using amount, the ethanol volume and the comprehensive score, and performing variance analysis by using a comprehensive score value model;
(6) And solving according to a model equation to obtain the optimal preparation condition of the colchicine alcohol transfersome.
2. The method of claim 1 for optimizing colchicine alcohol transfersomes by entropy weight in combination with a response surface method
Characterized in that in the step (1), the surfactant is tween 20 or sodium deoxycholate, and is preferably sodium deoxycholate.
3. The method of claim 1 for optimizing colchicine alcohol transfersomes by entropy weight in combination with a response surface method
Characterized in that in the step (1), the stirring temperature at constant temperature is 40 to 60 ℃, the rotation speed is 600 to 2000rpm, and the stirring time is 30 to 120min.
4. The method of claim 1 for optimizing colchicine alcohol transfersomes by entropy weight in combination with a response surface method
Characterized in that, in the step (4), the calculation steps of calculating the entropy value and the weight coefficient of each index by the objective entropy weight method are as follows:
(a) Index normalization processing: setting an original data matrix of n evaluation objects of m evaluation indexes as X = (aij) mn, normalizing the original data matrix to obtain X' = (xij) mn, and normalizing the positive indexes by the following formula;
x 'ij = (aij-min j { aij })/(max j { aij } -min j { aij }), wherein X' ij represents the value of the j-th evaluation index in the ith test, and i =1,2,3, \ 8230;, m; j =1,2,3, \8230;, n;
(b) Converting the original data matrix (aij) mn into a probability matrix (Pij) mn; pi in the information entropy formula is the probability of certain information, and satisfies that Pi is more than or equal to 0 and less than or equal to 1, so that the matrix (aij) mn must be normalized first, and the processed matrix can be regarded as a probability matrix of an evaluation index. Wherein Pij represents the probability of the jth test under the ith evaluation index;
(c) And calculating the entropy value of the index, and determining the information entropy (Hi) of the ith evaluation index.
(d) An entropy weight coefficient (Wj) of the index is calculated.
5. The method for optimizing the colchicine alcohol transfersome based on the response surface method in combination with the entropy weight method according to claim 1,
the method is characterized in that in the step (5), the model equation between the lecithin using amount, the surfactant using amount, the ethanol volume and the comprehensive score is obtained as follows: y =0.0416106+0.0105741A +0.00718237B +0.0108031C-0.00383408AB +0.0122264AC +0.00610334A 2 + 0.00390619B 2 + 0.0265679C 2 Using the comprehensive score value model to perform variance analysis and determine the coefficient r by an equation 2 = 0.7801。
6. The method of claim 1 for optimizing colchicine alcohol transfersomes by entropy weight in combination with a response surface method
Characterized in that in the step (6), the optimal preparation conditions of the colchicine alcohol transfersome are 500mg of lecithin, 50mg of sodium deoxycholate and 4mL of ethanol.
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