OPTIMIZATION, FORMULATION AND CHARACTERIZATION OF MICROSPHERES

Transcription

1 CHAPTER - 5 OPTIMIZATION, FORMULATION AND CHARACTERIZATION OF MICROSPHERES 5.1 Optimization of Method 5.2 Preparation of Microspheres 5.3 Characterization of Microspheres 5.4 Result & Discussion

2 OPTIMIZATION, FORMULATION & CHARACTERIZATION OPTIMIZATION OF METHOD Process optimization It is the discipline of adjusting a process so as to optimize some specified set of parameters without violating some constraint. The most common goals are minimizing cost, maximizing throughput, and/or efficiency. This is one of the major quantitative tools in industrial decision making. Traditional optimization methods generally study the effect of one variable at a time, because it is statistically easier to manipulate. However, in many cases, two factors may be interdependent, and it is impractical or false to attempt to analyze them in the traditional way. A 3 2 randomized full factorial design was adopted to optimize the variables The three-level design The three-level design is written as a 3 k factorial design. It means that k factors are considered, each at 3 levels. These are (usually) referred to as low, intermediate and high levels. These levels are numerically expressed as 0, 1, and 2. One could have considered the digits -1, 0, and +1. The reason that the three-level designs were proposed is to model possible curvature in the response function and to handle the case of nominal factors at 3 levels. A third level for a continuous factor facilitates investigation of a quadratic relationship between the response and each of the factors. In the present investigation two factors were evaluated, each at 3 levels (low, medium and high), and experimental trials were performed at all nine possible combinations. In the study, temperature (X 1 ) and stirring speed (X 2 ) were selected as independent variables. The particle size, % drug entrapment, and % Buoyancy were selected as dependent variables (80).

3 OPTIMIZATION, FORMULATION & CHARACTERIZATION Statistical Analysis Statistical analysis of factorial design batches was performed by multiple regression analysis using Microsoft Excel. To evaluate the contribution of each factor with different levels on responses, two way analysis of variance (ANOVA) followed by Tukey test was performed using Sigma Stat 2.03 (SPSS, Chicago, IL). To demonstrate graphically the influence of each factor (stirring speed and temperature) on dependent variables, response surface plot were generated, using Sigma Plot Software Version 8.0, (Jindal Scientific Software, San Rafeal, CA). The probability level p<5 was considered to be significant (81). 5.2 PREPARATION OF MICROSPHERES Microspheres were prepared by emulsification extraction technique. Pectin was used as a polymer and casein as emulsifier. The microspheres were prepared by modification of method described by Bulgareli et al. In preliminary batches 10 ml of 15% w/v (in different ratio) casein and pectin solution were added to 60ml Soya oil. Both oil and polymer solution was preheated separately up to 60 C. Each drug was added to the polymer emulsifier solution in two different quantities (50mg and 100mg) as shown in table 5.1 (a, b, and c). The mixture was mechanically stirred at 1000rpm to form o/w emulsion, after 5 min the solution was rapidly cooled at 15 C. 250ml of acetone was added to dehydrate & flocculate coacervate droplets. The microspheres was isolated by filtration through sintered glass filter. Residual oil over the microspheres was removed by washing with 250ml of acetone. After preparation of microspheres they were stored at room temperature in a dessicator at 8% relative humidity, otherwise drying conditions can influence microsphere release profile. Fifty millimeter diameter vessel, a three blade turbine rotator of 35 mm in diameter with digital stirring speed counter was selected (125, 126 and 127). In factorial design batches M1 to M9, D1 to D9 and F1 to F9, the polymer to emulsifier

4 OPTIMIZATION, FORMULATION & CHARACTERIZATION 115 ratio (1:1) and quantity of drug (100mg) was kept constant which was selected from preliminary batches. The temperature and stirring speed were varied in batches as shown in table 5.3 (a, b and c). All other variables were used as mentioned in preliminary trial batches. The effect of formulation variables on characteristics of the microspheres is summarized in Table 5.1 and 5.3 and in Figure 5.1 (a, b, and c), 5.2 (a, b, and c) and 5.3 (a, b, and c). Table 5.1(a): Results of preliminary trial batches of Methotrexate loaded Microsphere. Batch Code Polymer to Emulsifier Ratio (mg) Drug Quantity (mg) Drug Entrapment (%) Bouyancy (%) Particle Size and Sphericity MP1 1250: ±0.89 5±0.79 Small MP2 1000: ±7 59.0±0.63 Small MP3 750: ± ±0.95 Small/Spherical/Free flowing MP4 500: ± ±0.88 Large/Irregular MP5 250: ± ±0.92 Large/Irregular MP6 1250: ± ±0.80 Small MP7 1000: ± ±0.69 Small MP8 750: ± ±1.22 Small/Spherical/Free flowing MP9 500: ± ±0.96 Large MP10 250: ± ±0.87 Large/Irregular * n = 3, all values ± standard deviation, statistically significant at 5 level Table 5.1(b): Results of preliminary trial batches of Doxorubicin Loaded Microspheres Batch Code Polymer to Emulsifier Ratio (mg) Drug Quantity (mg) Drug Entrapment (%) Bouyancy (%) Particle Size and Sphericity DP1 1250: ±1.05 6±0.88 Small DP2 1000: ± ±0.63 Small DP3 750: ± ±0.77 Small/Spherical/Free flowing DP4 500: ± ±1.38 Large/Irregular DP5 250: ± ±1.29 Large/Irregular DP6 1250: ± ±0.95 Small DP7 1000: ± ±0.76 Small DP8 750: ± ±0.84 Small/Spherical/Free flowing DP9 500: ± ±0.94 Large DP10 250: ± ±0.60 Large/Irregular * n = 3, all values ± standard deviation, statistically significant at 5 level

5 OPTIMIZATION, FORMULATION & CHARACTERIZATION 116 Table 5.1(c): Results of preliminary trial batches of 5-Fluorouracil Loaded Microspheres Batch Code Polymer to Emulsifier Ratio (mg) Drug Quantity (mg) Drug Entrapment (%) Bouyancy (%) Particle Size and Sphericity FP1 1250: ± ±0.86 Small FP2 1000: ± ±0.93 Small FP3 750: ± ±1.05 Small/Spherical/Free flowing FP4 500: ± ±0.99 Large/Irregular FP5 250: ± ±1.04 Large/Irregular FP6 1250: ±0.84 6±0.95 Small FP7 1000: ± ±0.67 Small FP8 750: ± ±0.72 Small/Spherical/Free flowing FP9 500: ± ±1.21 Large/Irregular FP10 250: ±9 8±1.37 Large/Irregular * n = 3, all values ± standard deviation, statistically significant at 5 level 5.3 CHARACTERIZATION OF MICROSPHERES Quantitative Analysis of Microspheres The drug content of microsphers was determined by milling & immersing the microsphere of each drug, in distilled water after which they were stirred for 4 hrs & left at room temperature overnight. Filtered by using Whatmann filter paper, volume was made up by washing the residue & assayed in UV spectrophotometer. The absorbance was determined at λ max of respective drug against blank. The quantity of methotrexate, doxorubicin and 5-FU microencapsulated was calculated from standard calibration curve of drugs (61,62,64). The results are recorded in table 5.2(a, b, and c). Table 5.2(a): Drug Content Of Methotrexate Loaded Microsphere S. No Amount of Amount of % Yield Drug incorporated (mg) drug recovered (mg) M ± M ± M ± M ± M ± M ± M ± M ± M ± * n = 3, all values ± standard deviation, statistically significant at 5 level

6 OPTIMIZATION, FORMULATION & CHARACTERIZATION 117 Table 5.2(b): Drug Content Of Doxorubicin Loaded Microsphere S. No Amount of Amount of % Yield Drug incorporated (mg) Drug recovered (mg) D ± D ± D ± D ± D ± D ± D ± D ± D ± * n = 3, all values ± standard deviation, statistically significant at 5 level Table 5.2(c): Drug Content Of 5-Fluorouracil Loaded Microsphere S. No Amount of Amount of % Yield Drug incorporated (mg) Drug recovered (mg) F ± F ± F ± F ± F ± F ± F ± F ± F ± * n = 3, all values ± standard deviation, statistically significant at 5 level Determination Of Drug Entrapment Efficiency And Percentage Yield Microspheres 200mg were crushed in a dry glass pestle mortar, mixed with distilled water, and then filtered with 0.2m membrane filter and aliquot of the filtrate was diluted with distilled water. The filtrate was analyzed for drug content and absorbance was determined at λ max of respective drug by using blank The drug entrapment efficiency was calculated by the following formula (68, 69, 70). The results of preliminary and factorial batches are recorded in table 5.1(a, b, and c), and 5.3(a, b, and c) respectively for methotrexate, doxorubicin and 5-flourouracil microspheres. Percentage drug entrapment: {Practical drug content/ Theoretical drug content}*100 Percentage Yield: {Weight of microspheres /Weight of polymer and Drug}*100

7 OPTIMIZATION, FORMULATION & CHARACTERIZATION PARTICLE SIZE (MICROMETER) STIRRING SPEED (RPM) - - TEMPERATURE (C) Fig 5.1(a): Response Surface Plot Of Methotraxate Microsphere For Particle Size % Buoyancy Stirring Speed (rpm) - - Temperature (C) Fig 5.1(b): Response Surface Plot Of Methotraxate Microsphere % Buoyancy.

8 OPTIMIZATION, FORMULATION & CHARACTERIZATION % Drug Entrapment Stirring Speed (rpm) - - Temperature (C) Fig 5.1(c): Response Surface Plot Of Methotraxate Microsphere % Drug Entrapment Particle Size Stirring speed(rpm) - - Temperature(C) 1.0 Fig 5.2(a): Response Surface Plot Of Doxorubicin Microsphere For Particle Size

9 OPTIMIZATION, FORMULATION & CHARACTERIZATION 120 % Drug Entrapment Stirring Speed (rpm) - - Temperature (C) Fig 5.2(b): Response Surface Plot Of Doxorubicin Microsphere %Buoyancy Stirring Speed (rpm) - - Temperature (C) Fig 5.2(c): Response Surface Plot Of Doxorubicin Microsphere For % Bouyancy

10 OPTIMIZATION, FORMULATION & CHARACTERIZATION Particle Size Stirring Speed (rpm) - - Temperature (C) Fig No. 5.3(a) Response Surface Plot Of 5-FU Microsphere % Drug Entrapment Stirring Speed (rpm) - - Temperature (C) Fig 5.3(b): Response Surface Plot Of 5-FU Microsphere

11 OPTIMIZATION, FORMULATION & CHARACTERIZATION %Bouyancy Stirring Speed (rpm) - - Temperature (C) Fig 5.3(c): Response Surface Plot Of 5-FUMicrosphere Table 5.3(a): Formulation Characteristics Of Batches In A 3 2 Full Factorial Design* For Methotrexate Loaded Microspheres. Batch Code Coded Value Particle size (µm) Buoyancy (%) Drug Entrapment (%) X1 X2 M ± ± ±0.89 M ± ± ±0.48 M ± ± ±0.67 M ± ± ±0.29 M ± ± ±0.88 M ± ± ±0.64 M ± ± ±0.97 M ± ± ±0.48 M ± ± ±3 Coded Values Actual Values Variable levels X1 X Low Medium High * n = 3, all values ± standard deviation, statistically significant at 5 level. X 1 is temperature of both phases (ºC), and X 2 is stirring speed (rpm). All batches contained 200 mg methotrexate, 1.5% pectin and casein in ratio 1:1.

12 OPTIMIZATION, FORMULATION & CHARACTERIZATION 123 Table 5.3(b): Formulation Characteristics Of Batches In A 3 2 Design* For Doxorubicin Loaded Microspheres. Full Factorial Batch Code Coded Value Particle size (µm) Buoyancy (%) Drug Entrapment (%) X1 X2 D ± ± ±4 D ± ± ±0.49 D ±0.95 8± ±0.40 D ± ± ±8 D ± ± ±0.74 D ± ± ±0.38 D ± ± ±0.99 D ± ± ±0.28 D ±3 81.0± ±0.65 Coded Values Actual Values Variable levels X1 X Low Medium High * n = 3, all values ± standard deviation, statistically significant at 5 level. X 1 is temperature of both phases (ºC), and X 2 is stirring speed (rpm). All batches contained 200 mg methotrexate, 1.5% pectin and casein in ratio 1:1.

13 OPTIMIZATION, FORMULATION & CHARACTERIZATION 124 Table 5.3(c): Formulation Characteristics Of Batches In A 3 2 Full Factorial Design* For 5-Fluorouracil Loaded Microsphere. Batch Code Coded Value Particle size (µm) Buoyancy (%) Drug Entrapment (%) X1 X2 F ±7 38.0± ±9 F ± ±2 72.2±0.87 F ± ± ±0.66 F ± ± ±0.49 F ±0.88 7± ±5 F ± ± ±0.37 F ± ±9 73.3±0.82 F ± ± ±4 F ± ± ±0.74 Coded Values Actual Values Variable levels X1 X Low Medium High * n = 3, all values ± standard deviation, statistically significant at 5 level. X 1 is temperature of both phases (ºC), and X 2 is stirring speed (rpm). All batches contained 200 mg methotrexate, 1.5% pectin and casein in ratio 1:1.

14 OPTIMIZATION, FORMULATION & CHARACTERIZATION Determination Of Particle Size And Size Distribution The particle size of the microsphere was determined by using optical microscopy method. Approximately 500 particles were counted for particle size using a calibrated optical microscope. The particle size of preliminary batches and factorial batches for individual drug is reported in table 5.1 (a, b, and c) and 5.3 (a, b, and c), respectively for methotrexate, doxorubicin and 5-flourouracil microspheres (10, 11) Morphological Study Of Microspheres The shape and surface morphology of the microsphere was investigated using scanning electron microscopy as shown in figure 5.4 a, b, c, d, e and f for methotrexate, doxorubicin, 5-FU microspheres, surface of microspheres, and microspheres in group, respectively. Photomicrographs were taken at 50x magnification operated with an acceleration voltage of 10kV and working distance 9.1mm was maintained (89,92). 5.4(a): Methotrexate Microsphere 5.4(b): Doxorubicin Microsphere 5.4(c): 5-FU Microsphere 5.4(d): Surface Of Microsphere

15 OPTIMIZATION, FORMULATION & CHARACTERIZATION 126 Fig.5.4(e): Scanning Electron Photomicrograph Of Microspheres Fig.5.4(f): Scanning Electron Photomicrograph Of Microspheres

16 OPTIMIZATION, FORMULATION & CHARACTERIZATION Percentage Buoyancy Porous microspheres 200mg were spread over the surface of a USP XXIV paddle type dissolution apparatus filled with 900ml of buffer containing 2% v/v tween 20. The mixture was stirred at 100rpm. Particles were pipetted out and separated by filtration. Particles in sinking particulate layer were again separated by filtration. Particles of both type were dried in dessicator until constant weight was obtained. Both fractions of the microsphere were weighed and percentage buoyancy was determined by using following formula and the results are recorded in table 5.1 (a, b, and c), and 5.3 (a, b, and c), respectively for methotrexate, doxorubicin and 5-flourouracil microspheres (92). % Buoyancy = {[wf / wf + ws] x 100} Where, wf = weight of floating microspheres, ws = weight of sinking microspheres Stability Of Microsphere At Different Gastric ph Gastro-retentive floating microspheres are low-density systems that have sufficient buoyancy to float over gastric contents and remain in stomach for prolonged period where they are exposed to different ph and different enzymatic conditions which can influence their physicochemical properties and drug release behavior and can alter their stability characteristics. To test this hypothesis, drug loaded microspheres were subjected to different ph media where they encountered different ionic strengths and enzymatic conditions and the change in their properties was elucidated by counter checking their particle size. ph dependent stability studies were carried out in following media: 1. ph 1.1: 12 ml HCl (32%) with 1188 ml H 2 O 2. ph 3.5: 150 ml solution (1 g citric acid+100 ml NaOH (1 M) ml H 2 O) with 100 ml HCl 3. Simulated Gastric Fluid (SGF): 0.2% NaCl, Pepsin 0.7% HCl with ph 1.2

17 OPTIMIZATION, FORMULATION & CHARACTERIZATION 128 Ten milliliters of simulated fluid were added to 10 mg of microspheres. The samples were analyzed after a period of 8hrs in each of the above media. The above time intervals were selected for the study based on expected formulation residence time in stomach. Particle size was determined on the preset time periods (83). The results are recorded in table 5.4. Table 5.4: Initial And Final Particle Size After Exposure To Different Gastric ph. Medium Initial Size (µm) Final size (µm) MM DM FM MM DM FM ph ± ±0.37 5± ± ± ±0.88 ph ± ±0.37 5± ± ± ±3 SGF 59.60± ±0.37 5± ± ± ±0.41 MM- Methotrexate Microsphere, DM- Doxorubicin Microsphere, and FM- 5Flourouracil Microsphere, * n = 3, all values ± standard deviation, statistically significant at 5 level Fourier Transforms Infrared Spectroscopy Drug polymer interaction was studied by FT-IR spectroscopy (Shimadzu Affinity I, FT- IR spectrophotometer). The spectrum was recorded for pure drugs, loaded drug microspheres and unloaded microsphere (placebo). Samples were prepared by mixing 5% of drug or microsphere with 95% of KBr in glass pestle mortar. The scanning range was 4000 cm -1 to 400 cm -1 and resolution was 2 cm -1(79). The spectra are recorded in figure 5.5(a, b, c and d) Flow Properties Flow properties were determined in terms of Carr s index (I c ) and Hausner s ratio (H R ). The Carr index is an indication of the compressibility of a powder. The Carr index is frequently used in pharmaceutics as an indication of the flowability of a powder. A Carr s index greater than 25 is considered to be an indication of poor flowability, and below 15, of good flowability I c = ρ t - ρ b / ρ t Where, ρ t = tapped density ρ b = bulk density

18 OPTIMIZATION, FORMULATION & CHARACTERIZATION %T Fig 5.5(a): FTIR Spectra Of Plecebo Microsphere /cm 25.5 %T Fig 5.5(b): FTIR Spectra Of Methotrexate Microsphere /cm

19 OPTIMIZATION, FORMULATION & CHARACTERIZATION %T Fig 5.5(c): FTIR Spectra Of Doxorubicin Microsphere /cm 33 %T Fig 5.5(d): FTIR Spectra of 5FU Microsphere /cm

20 OPTIMIZATION, FORMULATION & CHARACTERIZATION 131 Table 5.5: Angle Of Repose, Carr s Index And Hausner s Ratio As An Indication Of Flow Properties. Angle of repose (θ) Carr s index (%) Hausner s ratio Type of flow > Excellent <1.25 Good Fair to passable >1.25 Poor Very poor >40 >40 - Extremely poor Table 5.6(a): Micromeritic Properties Of Methotrexate Microsphere. Code Angle of Repose (ө) Carr s Index (%) Hausner s Ratio M ± ± ±15 M ± ± ±21 M ± ± ±40 M ± ± ±28 M ± ± ±19 M6 23± ± ±42 M ± ± ±24 M ± ± ±33 M ± ± ±35 * n = 3, all values ± standard deviation, statistically significant at 5 level Table 5.6(b): Micromeritic Properties Of Doxorubicin Microspheres. Code Angle of Repose (ө) Carr s Index (%) Hausner s Ratio D ± ± ±42 D ± ± ±25 D ± ± ±26 D ± ± ±47 D ± ± ±38 D ± ± ±54 D ± ± ±35 D ± ± ±22 D ± ± ±48 * n = 3, all values ± standard deviation, statistically significant at 5 level Table 5.6(c): Micromeritic Properties Of 5-FU Microspheres. Code Angle of Repose (ө) Carr s Index (%) Hausner s Ratio F ± ± ±25 F ± ± ±34 F ± ± ±47 F ± ± ±32 F ± ± ±56 F ± ± ±49 F ± ± ±65 F ± ± ±32 F ± ± ±45 * n = 3, all values ± standard deviation, statistically significant at 5 level

21 OPTIMIZATION, FORMULATION & CHARACTERIZATION 132 The Carr index is related to the Hausner ratio, another indication of flowability, by the formula: H R = ρ t / ρ b The Hausner ratio and Carr s index are both measures of the flow properties of powders. A Hausner ratio of <1.25 indicates a powder that is free flowing whereas >1.25 indicates poor flow ability. The smaller the Carr s Index the better the flow properties. For example 5-15 indicates excellent, good, fair and > 23 poor flow (128). The angle of repose (θ) of the microsphere, which measures the resistance to particle flow, was determined by the fixed funnel method, using the following equation: tan θ = 2H/D Where, 2H/D is the surface area of the free standing height of the heap that formed after making the microspheres flow from the glass funnel (129). When bulk granular materials are poured onto a horizontal surface, a conical pile will form. The internal angle between the surface of the pile and the horizontal surface is known as the angle of repose and is related to the density, surface area and shapes of the particles, and the coefficient of friction of the material. Material with a low angle of repose forms flatter piles than material with a high angle of repose. Fixed Funnel Method The material is poured through a funnel to form a cone. The tip of the funnel should be held close to the growing cone and slowly raised as the pile grows, to minimize the impact of falling particles. Stop pouring the material when the pile reaches a predetermined height or the base a predetermined width. Rather than attempt to measure the angle of the resulting cone directly, divide the height by half the width of the base of the cone. The inverse tangent of this ratio is the angle of repose. The results are recorded in table 5.6.

22 OPTIMIZATION, FORMULATION & CHARACTERIZATION RESULT AND DISCUSSION Porous microspheres of drugs were successfully prepared by emulsification extraction method. A statistical model incorporating interactive polynomial term was used to evaluate the response Y = b 0 + b 1 X 1 + b 2 X 2 + b 12 X 1 X 2 + b 11 X 11 + b 22 X 22 Where, Y is the dependent variable, b0 is the arithmetic mean response of nine runs, b 1 is the estimated coefficient for the factor X 1. The main effects (X 1 and X 2 ) represent the average results of changing one factor at a time from its low to high value. The interaction terms (X 1 X 2 ) show how the responses change when two factors are simultaneously changed. The polynomial terms (X 1 X 1 and X 2 X 2 ) are included to investigate nonlinearity. The fitted equation relating the responses particle size, % drug entrapment, and % buoyancy to the transformed factor are shown in equation 1, 2, 3, 4, 5, 6, 7, 8, and 9 for methotrexate, doxorubicin HCl and 5-FU microspheres respectively. PS = 1.06 x x 1 x x x x Eq-1 %DE = x x 1 x x x x Eq-2 %B = -0.2 x x 1 x x x x Eq-3 PS = x x 1 x x x x %DE = x x 1 x x x x Eq-4 Eq-5 %B = -5 x x 1 x x x x Eq-6 PS = x x 1 x x x 1-21 x %DE = -6 x x 1 x x x x Eq-7 Eq-8 %B = 1.15 x x 1 x x x x Eq-9 To demonstrate graphically the effect of the temperature and stirring speed, the response surface plots Figure 5.1(a, b, c), 5.2(a, b, c), and 5.3(a, b, c) were generated for the

23 OPTIMIZATION, FORMULATION & CHARACTERIZATION 134 dependent variables, particle size, % drug entrapment and %buoyancy using Sigma Plot software. Results of ANOVA for the measured responses are provided in Table 5.10, 5.11 and The statistical analysis of the factorial design batches was performed by multiple polynomial regression analysis using Microsoft Excel. The data clearly depicts that the Particle size (PS), % drug entrapment (%DE), and % Buoyancy (%B) values are strongly dependent on the selected independent variables. The polynomial equations can be used to draw conclusions after considering the magnitude of coefficient and the mathematical sign it carries (positive or negative). The value of the correlation coefficient indicates a good fit (Table 5.7, 5.8 and 5.9). Table 5.7: Multiple Regression Output for Dependent Variables* (methotrexate microsphere). Parameters Coefficient of Regression Parameters B 0 b 1 b 2 B 12 b 11 b 22 r P PS <01 %EE <01 %B <01 PS, particle size; %EE, % drug entrapment; %B, % buoyancy. Table 5.8: Multiple Regression Output for Dependent Variables*(doxorubicin microsphere) Parameters Coefficient of Regression Parameters B 0 b 1 b 2 b 12 b 11 b 22 r P PS <01 %EE <01 %B <01 PS, particle size; %EE, % drug entrapment; %B, % buoyancy. Table 5.9: Multiple Regression Output for Dependent Variables*(5-flourouracil microspheres) Parameters Coefficient of Regression Parameters B 0 b 1 b 2 b 12 b 11 B 22 r P PS <01 %EE <01 %B <01 PS, particle size; %EE, % drug entrapment; %B, % buoyancy.

24 OPTIMIZATION, FORMULATION & CHARACTERIZATION 135 Table 5.10: Results of Analysis of Variance for Measured Response* (methotrexate microspheres). Parameters df SS MS F Significance F For PS Regression <01 Residual Total For %EE Regression <01 Residual Total For %B Regression <01 Residual Total *df indicates degree of freedom; SS, sum of square; MS, mean sum of square; and F, Fischer s ratio. Table 5.11: Results of Analysis of Variance for Measured Response* (doxorubicin HCl microspheres). Parameters df SS MS F Significance F For PS Regression <02 Residual Total For %EE Regression <06 Residual Total For %B Regression <01 Residual Total *df indicates degree of freedom; SS, sum of square; MS, mean sum of square; and F, Fischer s ratio.

25 OPTIMIZATION, FORMULATION & CHARACTERIZATION 136 Table 5.12: Results of Analysis of Variance for Measured Response* (5-FU microspheres). Parameters df SS MS F Significance F For PS Regression <01 Residual Total For %EE Regression <01 Residual Total For %B Regression <01 Residual Total *df indicates degree of freedom; SS, sum of square; MS, mean sum of square; and F, Fischer s ratio. To evaluate the contribution of different levels of factor (X 1 ) and factor (X 2 ), 2-way ANOVA followed by Tukey test was performed using Sigma Stat software. Results of two-way ANOVA for the both factors at different levels are provided in Table 5.13, 5.14 and Where p is the parameter used when computing q. The larger the p, the larger q needs to be to indicate a significant difference. p is an indication of the differences in the ranks of the group means being compared. Groups means are ranked in order from largest to smallest, and p is the number of means spanned in the comparison. For example, when comparing four means, comparing the largest to the smallest p = 4, and when comparing the second smallest to the smallest p = 2. If a group is found to be not significantly different than another group, all groups with p ranks in between the p ranks of the two groups that are not different are also assumed not to be significantly different, and a result of DNT (Do Not Test) appears for those comparisons. The Difference of Means is a gauge of the size of the difference between the groups or cells being compared.

26 OPTIMIZATION, FORMULATION & CHARACTERIZATION 137 Table 5.13: Results of two way ANOVA for factors X1 and X2 at different levels (methotrexate microspheres). Particle size Factor X1 Comparison Diff of Means p q P P<50 00 vs Yes 00 vs Yes 00 vs No Factor X2 00 vs <01 Yes 00 vs Yes 00 vs Yes %Drug entrapment Factor X vs <01 Yes vs Yes 00 vs Yes Factor X vs No vs Do Not Test 00 vs Do Not Test % Bouyancy Factor X vs Yes vs No 00 vs Yes Factor X vs <01 Yes vs Yes 00 vs Yes X 1 is temperature of both phases (ºC), and X 2 is stirring speed (rpm) p is a parameter used when computing q. The larger the p, the larger q needs to be to indicate a significant difference. p is an indication of the differences in the ranks of the group means being compared. Groups means are ranked in order from largest to smallest, and p is the number of means spanned in the comparison.

27 OPTIMIZATION, FORMULATION & CHARACTERIZATION 138 Table 5.14: Results of two way ANOVA for factors X1 and X2 at different levels (doxorubicin HCl microspheres). Particle size Factor X1 Comparison Diff of Mean p q P P<50 00 vs No 00 vs Do Not Test 00 vs Do Not Test Factor X2 00 vs <01 Yes 00 vs No 00 vs <01 Yes % Drug entrapment Factor X1 00 vs Yes 00 vs No vs Yes Factor X vs Yes vs Yes 00 vs Yes % Bouyancy Factor X vs <01 Yes vs <01 Yes 00 vs <01 Yes Factor X vs <01 Yes vs <01 Yes 00 vs <01 Yes X 1 is temperature of both phases (ºC), and X 2 is stirring speed (rpm).

28 OPTIMIZATION, FORMULATION & CHARACTERIZATION 139 Table 5.15: Results of two way ANOVA for factors X1 and X2 at different levels (5- Fluorouracil microspheres). Particle size Factor X1 Comparison Diff of Mean p q P P<50 00 vs Yes 00 vs Yes 00 vs Yes Factor X2 00 vs <01 Yes 00 vs <01 Yes 00 vs <01 Yes % Drug entrapment Factor X vs Yes vs No 00 vs Yes Factor X vs Yes vs Yes 00 vs Yes % Bouyancy Factor X vs <01 Yes vs <01 Yes 00 vs No Factor X vs <01 Yes vs <01 Yes 00 vs Yes X 1 is temperature of both phases (ºC), and X 2 is stirring speed (rpm).

29 OPTIMIZATION, FORMULATION & CHARACTERIZATION 140 The porous microspheres of pectin were prepared by emulsification extraction technique. Pectin was selected as polymer for the preparation of porous microspheres owing to its biodegradable nature and stability at lower ph properties. In preliminary batches different ratio of polymer to emulsifier was used for preparing the polymer solution, the polymer solution was too viscous at ratio 1250:250 and 1000: 500 (pectin: casein) and difficult to pour in oil. As well as quantity of polymer increased from mg in polymer to emulsifier ratio, percentage entrapment efficiency of microspheres increased with low % buoyancy. On the other hand if quantity of emulsifier was raised 250 to 1250 in polymer to emulsifier ratio, microspheres produced were irregular and of large size with increased buoyancy and with less entrapment efficiency. Therefore 750:750 (1:1) ratio of pectin to casein was found to be optimum concentration of polymer and emulsifier which provide microspheres of small size with good % entrapment efficiency and increased % buoyancy. Two different quantities of drug 50mg and 100mg were used for preparation of microspheres. 100mg of drug can be easily incorporated in microspheres, but no significant effect of amount of drug on % entrapment efficiency and on % buoyancy were seen (table 5.1 a, b and c). On the basis of preliminary trials 3 2 full factorial design was employed to study the effect of independent variables temperature and stirring speed on dependent variables particle size, percentage buoyancy and percentage drug entrapment efficiency. The results were depicted in Table 5.3 (a, b, and c) and in Figure 5.1(a, b, and c), 5.2 (a, b, and c), and 5.3 (a, b, and c). Microspheres were characterized for drug content. Drug content ranges from 95.40±0.45 to 97.54±0.48, 78.1±0.42 to 79.2±3 and 90.24±0.65 to 94.90±0.34, respectively for methotrexate microsphere, doxorubicin microsphere and 5-FU microspheres. The maximum % drug entrapment was found to be 95.40±0.89 to

30 OPTIMIZATION, FORMULATION & CHARACTERIZATION ±3, 72.97±4 to 75.99±0.38 and 72.2±0.87 to 73.3±0.74 methotrexate microsphere, doxorubicin microsphere and fluorouracil microsphere, respectively. The results are presented in table 5.2 (a, b, and c). This proves that emulsification extraction technique is a proper method of preparation of porous microspheres and that the polymers and oil have been rightly selected. Particle size and surface morphology were assessed by scanning electron microscopy. Photomicrographs showed that microspheres are spherical with rough surface. It was observed that the particle size of methotrexate microspheres, doxorubicin microspheres and 5- fluorouracil microspheres were ±0.23 to 59.60±0.95, 94.2±0.66 to 55.0±0.44 and 102.0±7 to 5±0.86 micrometer, respectively. The results were depicted in table 5.3 (a, b, and c). Size of microspheres greatly affects the flow properties. Particles or microspheres having a smaller size showed good flow properties as shown in Figure 5.4 (a, b, c and d). The % Buoyancy was found to be 74.2±0.23 to 82.0±0.27, 73.2±0.47 to 82.0±0.29 and 38.0±0.63 to 76.0±0.36 for methotrexate microspheres, doxorubicin microspheres and 5-fluorouracil microspheres, respectively. The results were depicted in Table 5.3 (a, b, and c). The GI stability of the particles was investigated by suspending the particles to simulated GI fluids and found to be quite stable (Table 5.4) under the study conditions and duration. This formed an important exercise, as stable particles would remain floated and result in increase in subsequent bioavailability of drug. Figure 5.5 (a, b, c and d) are the characteristic peaks of the plecebo microspheres and drug loaded microspheres. Drug polymer interaction was studied by FT-IR spectroscopy. The spectrum was recorded for pure drugs, loaded drug microspheres and unloaded microspheres (placebo). Samples were prepared by mixing 5% of drug or microspheres with 95% of KBr in glass pestle mortar. The scanning range was 4000 cm -1

31 OPTIMIZATION, FORMULATION & CHARACTERIZATION 142 to 400 cm -1 and resolution was 2 cm -1. The peaks which are present in spectra of placebo microspheres are similar to that of drug loaded microspheres. FTIR analysis reveals that complete encapsulation of drug occurs in microspheres. Flow properties of the formulations were determined and it is found that angle of Repose, Housner s Ratio and Car s Index, for methotrexate microsphere was 20.32±0.432 to 27.36±0.690, 11.01±0.342 to 17.17±0.241, and 1.135±35 to 1.164±15, respectively. For doxorubicin microsphere it was 22.67±0.325 to 29.43±0.432, 11.63±0.362 to 15.13±0.343, and 1.139±54 to 1.166±42 respectively. For 5- fluorouracil microsphere it was 20.23±0.867 to 27.03±43, 11.23±43 to 16.42±62 and 1.132±45 to 1.173±25, respectively. Angle of repose is defined as the miximum angle possible between the surface of a pile of the powder and the horizontal plane. The lower the angle of repose, better the flow property. The rough and irregular surface of particles gives higher angle of repose. The Hausner ratio and Carr s index are both measures of the flow properties of powders. A Hausner ratio of <1.25 indicates a powder that is free flowing whereas >1.25 indicates poor flow ability. The smaller the Carr s Index the better the flow properties. For example 5-15 indicates excellent, good, fair and > 23 poor flow. So for the optimized formulation angle of repose is low, Hausner ratio of <1.25 and smaller Carr s Index which means the formulations are free flowing. The results are shown in table 5.6. From the results of Tukey test, it was found that both factor X1 and X2 had significant effect on particle size, % buoyancy and % drug entrapment at different levels as shown in table 5.13, 5.14 and 5.15.