Results and Discussion

Transcription

1 NASAL NANOCARRIER DELIVERY SYSTEM FOR THE TREATMENT OF OSTEOPOROSIS Results and Discussion Chapter 5

2 5.1. PHYSICAL CHARACTERIZATION AND IDENTIFICATION OF RALOXIFENE HCl Organoleptic properties Raloxifene HCl was found to be crystalline, pale-yellow coloured, odourless and pungent in taste solid powder Solubility The solubility of raloxifene HCl in water was found to be ± µg/ml (in distilled water ph ( ) (reported value ± µg/ml) (Jansen, 2009) Partition coefficient The partition coefficient of raloxifene HCl was found to be 1315 ± 46 (reported value 1323±91) (Trontelj et al., 2005) Loss on drying The loss on drying for raloxifene HCl was found to be 0.3% (should not be > 0.5%). Hence, the loss on drying of the drug samples was found to be in the limit IR spectroscopy Fig.5.1. IR spectra of raloxifene HCl reference standard and API The IR spectrum of raloxifene HCl was found to be similar with the reference spectra and Department of Pharmaceutics 91 Jamia Hamdard

3 is shown in Fig.5.1.The IR spectra given in Fig.5.1. revealed that raloxifene HCl has characteristic absorption bands at 3506, 3378, 3251, 2952, 2669, 1572, 1490, 1438, 1366, 1143, 966, 816, 572, 526 and 507 cm -1 which was found to be in agreement with reported IR spectrum or raloxifene HCl (Pathi, 2011) Differential scanning calorimetery (DSC) DSC analysis was carried out and sample of raloxifene HCl was scanned between ºC at a heating rate of 10 ºC/ min, under nitrogen atmosphere, using a Differential Scanning Calorimetery, Pyris 6 DSC (Perkin Elmer, CT, USA). The resultant thermogram was recorded and is shown in Fig Fig.5.2.DSC thermogram of raloxifene HCl The thermogram revealed that raloxifene HCl is crystalline substances with sharp endothermic peaks at ºC corresponding to its melting points. The obtained thermogram was found to be in agreement with reported thermogram of raloxifene HCl ((Pathi, 2011).) X-Ray-Diffraction Studies X-ray powder diffraction spectrum given in Fig revealed that raloxifene HCl has the following peaks at diffraction degrees (2θ): 6.69, 14.4, 15.3, 19.0, 21.1 and The XRD spectral analysis showed similar peaks as of the reference product. Department of Pharmaceutics 92 Jamia Hamdard

4 Fig.5.3. XRD of raloxifene HCl reference standard and API Particle size determination The particle size of the drug was obtained using a Malvern Particle Size Analyzer (Malvern Mastersizer, UK). The resultant spectrum of raloxifene HCl was recorded and is shown in Fig.5.4. having D(0.9), D(0.5) and D(0.1) as 43.11, and respectively Surface area determination Fig.5.4. PSD of raloxifene HCl BET surface area plot of raloxifene HCl was recorded and is shown in Fig. 5.5 which was found to be m 2 /g. Department of Pharmaceutics 93 Jamia Hamdard

5 Fig.5.5. BET surface area plot of raloxifene HCl Conclusion: On the basis of above physicochemical characterization and identification it was concluded that the drug obtained was an authentic sample of raloxifene HCl COMPATIBILITY STUDIES Physical Characterization: The raloxifene HCl excipients compatibility studies were carried out by visual observations for any colour change, lump formation, gas formation and liquification. Visual observation results are shown in Table 5.1. Department of Pharmaceutics 94 Jamia Hamdard

6 Table 5.1. Physical characterization of drug excipients compatibility study Intial Control 40 C/75 % 40 C/ C 60 C Sample sample RH Open % RH Open (30 Closed (30 (30 days) (30 days) Closed (30 days) days) days) API:Chitosan Pale yellow No No change No change No change No change (1:2) API:TPP (1:2) Pale yellow change No change No change No change No change No change API:PLGA (1:2) Pale yellow No change Slight Liquification Slight Liquification Slight Liquification Slight Liquification API:PVA (1:2) Pale yellow No change No change No change No change No change Chitosan White powder No change No change No change No change No change TPP White powder No change No change No change No change No change PLGA Transparent crystals No change Slight Liquification Slight Liquification Slight Liquification Slight Liquification PVA White powder No change No change No change No change No change API: Active pharmaceutical ingredient; TPP: Sodium Tripolyphosphate; PLGA: Poly (D-L lactide- co- glycolide); PVA: Polyvinyl alcohol Department of Pharmaceutics 95 Jamia Hamdard

7 DSC of Drug Excipients Compatibility Study:\ Fig.5.6. DSC thermogram API: TPP (1:2) and TPP Fig.5.7. DSC thermogram API: chitosan (1:2) and chitosan Department of Pharmaceutics 96 Jamia Hamdard

8 Fig.5.8. DSC thermogram API: PLGA (50:50) (1:2) and PLGA Fig.5.9. DSC thermogram API: PVA (1:2) and PVA Conclusion: No notable change was observed in the samples on visual observation. There was no observable colour change or gas formation. No peak shifting in DSC of the drug-excipients mix was noticed. The DSC thermogram of physical mixture of drug excipients revealed thermal events (peaks) corresponding to a combination of individual thermograms of both. Department of Pharmaceutics 97 Jamia Hamdard

9 And thus, absence of any significant changes suggested a possible compatibility of raloxifene HCl with selected excipients ANALYTICAL METHODOLOGY FOR RALOXIFENE HCl RP-HPLC Method Development RP-HPLC method was developed and validated to determine raloxifene HCl quantitatively in the concentration range of 0.1 to 50 µg/ml for routine analysis, for determining the drug entrapment efficiency, drug loading, assay and in vitro drug release for the prepared formulations. For mobile phase, ammonium formate resulted in high sensitivity compared with ammonium acetate buffer, Phosphate buffer and phosphoric acid solution. Formic acid (0.05%) with 1 mm ammonium formate resulted in the best peak shape as compared to the mobile phase having ammonium formate that resulted in broad peak shape. Acetonitrile was used as organic modifier as it resulted in better sensitivity and improved the peak symmetry (about 1.08). Columns from different sources were evaluated, and the Phenomenex Luna C 18 analytical column was selected, as it provided the best chromatographic performance and acceptable peak characteristics, including tailing factor, number of theoretical plates, and capacity factor. For selection of the best wavelength of detection, a PDA detector was used. Chromatograms of raloxifene HCl standard solution (50 µg/ml), LOQ and mobile phase devoid of raloxifene HCl are shown in Fig The regression equation obtained was y = x+1.42 with the correlation coefficient (r 2 ) of , where y represents peak area and x represents the concentration of raloxifene HCl bulk drug (µg/ml). Department of Pharmaceutics 98 Jamia Hamdard

10 Fig Chromatograms of raloxifene HCl, peak 1= raloxifene HCl (a) raloxifene HCl standard solution (50 µg/ml), (b) LOQ and (c) mobile phase devoid of raloxifene HCl Calibration curve of raloxifene HCl by RP-HPLC method The linear regression data shown in Fig. 5.11, for the calibration curves (n=3) as shown in Table 5.2 and Table 5.3 showed a good linear relationship over concentration range µg /ml with respect to the peak area. There was no significant difference observed in the slopes of standard curves (ANOVA, p > 0.05). Department of Pharmaceutics 99 Jamia Hamdard

11 Table 5.2. Calibration curve data for raloxifene HCl Concentration Mean peak area % RSD (µg /ml) ± S.D. (n = 3) ± ± ± ± ± ± ± ± Table Linear regression data for the calibration curve (n=3) Parameters (n=3) Results %RSD %Range (µg/ml) Slope Intercept r LOD (µg/ml) 0.05 LOQ (µg/ml) 0.1 Fig Calibration curve for raloxifene HCl by RP-HPLC method Method Validation of Raloxifene HCl by RP-HPLC method The newly developed RP-HPLC method was validated in terms of system suitability, linearity, limit of detection (LOD), limit of quantification (LOQ), accuracy, precision, robustness, specificity and stability according to International Conference of Harmonization Department of Pharmaceutics 100 Jamia Hamdard

12 of Technical Requirements for registration of Pharmaceuticals for Human use (ICH) guidelines System suitability-the acceptance criteria in the system suitability test were ± 2% for the % CV for the parameters studied. The % CV of peak area, retention time, theoretical plates, capacity factor, and tailing factor (peak symmetry) for drug were within acceptable range, indicating the suitability of the system as shown in Table 5.4. Table 5.4. System suitability study Raloxifene HCl (5 µg/ml) Theoretical plate Peak Area Retention time (min) Tailing factor Capacity factor Mean (n=6) S.D % CV Linearity-The calibration curves were constructed with eight concentrations in triplicate including the LOQ ranging from 0.1 to 50 µg/ml. The peak area of the drug was plotted against the concentration. The regression equation obtained is y = x with the correlation coefficient (r 2 ) of The results showed excellent correlation between the peak area and concentration of raloxifene HCl bulk drug as summarized in Table LOQ and LOD-LOQ was determined at a sound-to-noise ratio of 10 whereas LOD was determined at sound-to-noise ratio of 3. LOQ value for raloxifene HCl was found to be 0.1 µg/ml with a signal-to-noise ratio of The LOD value for raloxifene HCl bulk drug was found to be 0.05 µg/ml with a signal-to-noise ratio of Accuracy and precision-accuracy and precision calculated for the QC samples during the intra- and inter-day run are shown in Table 5.5. The intra-day (day 1) accuracy ranged from -2.39% to 3.19% and precision from 0.35% to 2.30%. The results obtained from intermediate precision (inter-day) also indicated a good method precision. All the data were within the acceptance criteria of 5% (except 10% for LOQ). Department of Pharmaceutics 101 Jamia Hamdard

13 Table 5.5. Intra-and inter-day accuracy and precision of RP-HPLC assay for raloxifene HCl Nominal concentration (µg/ml)* Day 1 Mean S.D % CV Accuracy (% Bias) Day 2 Mean S.D % CV Accuracy (% Bias) Day 3 Mean S.D % CV Accuracy (% Bias) *Each mean value is the result of triplicate analysis Robustness-To determine the robustness of the method the experimental conditions were deliberately changed and the resolution of raloxifene HCl was evaluated. The mobile phase flow rate was 1 ml/min; to study the effect of flow rate on resolution it was changed to 0.9 and 1.1 ml/min. The effect of column temperature was studied at 25 ºC and 35 ºC (instead of 30 ºC). The wavelength used for quantification was 286 and 288 nm. But in all the deliberately varied chromatographic conditions, the performance of the methods was found unaffected. Thus, the method was found robust with respect to variability in above conditions Stability-Stability studies indicated that the samples were stable when kept at bench top for 12 h (short-term), in auto-sampler for 24 h and refrigerated at 4 ºC for 30 days (long-term). The results of these stability studies are shown in Table 5.6., where the percent ratios are within the acceptance range of %. Department of Pharmaceutics 102 Jamia Hamdard

14 Table 5.6. Short-term, long-term and auto-sampler stability of raloxifene HCl Nominal concentration (µg/ml)* Short-term stability Mean S.D % CV long-term stability Mean S.D % CV auto-sampler stability Mean S.D % CV *Each mean value is the result of triplicate analysis UPLC Method Development for raloxifene HCl Development of mobile phase The aim to develop UPLC method was to separate raloxifene HCl and its degradation product formed during forced degradation studies and to elute raloxifene as a symmetrical peak. To obtain the best chromatographic conditions, the mobile phase was optimized to provide sufficient selectivity and sensitivity which efficiently separated raloxifene and its degradation product. Formic acid (0.1%) in water resulted in the best peak shape as compared to the mobile phase with having ammonium acetate buffer, Phosphate buffer and phosphoric acid solution that resulted in broad peak shape. Different Columns were evaluated, and the Waters Acquity BEH C 18, mm, 1.7 µm column analytical column was selected, as it provided the best chromatographic performance and acceptable peak characteristics. Gradient elution was optimized for method development as it was difficult to separate the degradation products in isocratic mobile phase. Acetonitrile was used as organic modifier as it resulted in better sensitivity and improving the peak symmetry (about 1.08). Moreover, acceptable resolution of raloxifene and the degradation products was obtained, confirming the stability-indicating capability of the proposed method. It was found that use of solvent A and solvent B with gradient elution (time (min) /% solvent B: 0/10, 0.01/10, 0.3/10, 2.8/40, 3.0/50, 3.5/95, 4.5/95, 4.8/10 and 6.0/10) gave enabled separation for all degradation products and eluted raloxifene as a symmetrical peak. Interference from the excipients was also studied; no interference was observed as shown in Department of Pharmaceutics 103 Jamia Hamdard

15 Fig Fig UPLC Chromatogram of raloxifene: (from top to bottom) (a)standard solution (10µg/ml), (b)extracted from nanoparticulate formulation (10µg/mL), (c) LOQ and (d) mobile phase devoid of raloxifene Method validation of UPLC method System suitability The acceptance criteria in the system suitability test were ±2% for the % RSD for the parameters studied. The % RSD of peak area, retention time, theoretical plates and tailing factor (peak symmetry) for drug were within acceptable range, indicating the suitability of the system as shown in Table 5.7. Table 5.7. Evaluation of system suitability a Injection no. RT(min) Peak area Plate count USP tailing Mean %RSD a Replicate injection of 10 µg/ml standard Linearity The calibration curves were constructed with eight concentrations in triplicate including the LOQ ranging from 0.1 to 50 µg/ml. The peak area of the drug was plotted against the concentration. The regression equation obtained was y = x with the Department of Pharmaceutics 104 Jamia Hamdard

16 correlation coefficient (r 2 ) of The results showed excellent correlation between the peak area and concentration of raloxifene bulk drug as summarized in Table 5.8. Table 5.8. Results of regression analysis of linearity data of raloxifene Parameters (n=3) Results %RSD %Range (µg/ml) slope Intercept r LOD (µg/ml) LOQ (µg/ml) LOQ and LOD LOQ was determined at a sound-to-noise ratio of 10 whereas LOD was determined at sound-to-noise ratio of 3. LOQ value for raloxifene was found to be 0.1 µg/ml with a signal-to-noise ratio of The LOD value for raloxifene bulk drug was found to be µg/ml with a signal-to-noise ratio of 9. Data is represented in Table Precision The precision of the assay method was evaluated as repeatability and intermediate precision by carrying out six independent assays at QC samples of raloxifene on different days by different analysts. For repeatability, the % relative standard deviation (% RSD) of raloxifene was found to be in a range of whereas the % RSD of assay results obtained in intermediate precision study was in the range of (Table 5.9.). These % RSD values are well within the generally acceptable limit of 2%, confirming good precision of the assay method. Table 5.9. UPLC method precision Intermediate precision Repeatability Inter-day measured conc. Different analyst measured conc. Inter-day measured conc. Avg. % RSD Avg. conc. % RSD Avg. conc. % RSD Theoretical conc. (µg/ml) conc. rec.* (µg/ml) rec.* (µg/ml) rec.* (µg/ml) *Average concentration recovered (n=6) Department of Pharmaceutics 105 Jamia Hamdard

17 Accuracy Triplicate injections were made at specified concentrations to assess the accuracy of the method. The accuracy of the method was assessed by back calculation of the injection peak areas using the derived calibration curves to give the calculated concentration for each injection. These values were compared to the theoretical value derived from the linear curve and reported in terms of % deviation from the theoretical value (RSD, Table 5.10.). The range of the method was established from 0.1 to 50 µg/ml. Table UPLC method accuracy Theoretical conc. (µg/ml) Recovery (µg/ml)* % Recovery % RSD *Average concentration recovered (n=6) Robustness To determine the robustness of the method the experimental conditions were deliberately changed and the resolution of raloxifene was evaluated. The mobile phase flow rate was 0.35 ml/min; to study the effect of flow rate on resolution it was changed to 0.30 and 0.40 ml/min. The effect of column temperature was studied at 28 ºC and 32 ºC (instead of 30 ºC). Wavelength used for quantification was 286 and 288 nm. In all the deliberately varied chromatographic conditions, the performance of the methods was found unaffected. Thus, the method was found robust with respect to variability in above conditions Specificity Stress testing of drug substance can help in identifying the likely degradation products, the stability of the molecule and also validate the stability and specificity of the analytical procedures. Stress studies were performed at an initial concentration 100 µg/ml of raloxifene to provide an indication of the stability-indicating property and specificity of the proposed method. Stress studies were performed using the following conditions: acid degradation (1 N HCl at 60 ºC for 8 h), alkaline degradation (1 N NaOH at 60 ºC for 8 h), oxidation (20% H 2 O 2 ), photolytic (UV light at 254 nm for 8 h), water hydrolysis (60 ºC for 8 h) and reductive degradation (Zn in 1 N HCl at 60 ºC for 1 h). Department of Pharmaceutics 106 Jamia Hamdard

18 All forced degradation samples were analyzed at an initial concentration 50 µg/ml of raloxifene with mentioned UPLC conditions. Degradation was not observed when raloxifene was subjected to base, acid, light, oxidation and water hydrolysis. Significant degradation was observed when the drug was subjected to reduction (Zn in 1 N HCl at 60 ºC for 1 h) leading to the formation of various degradation products (Fig ). LC MS/MS analysis was performed as per experimental conditions and mass of the various degradation products were determined. The m/z of parent molecule was 474 which retain at 2.89 min while the degradation product has m/z and 462 having RT 2.67 min and 3.30 min respectively. Degradation product A (m/z ) was generated by reduction of - C=O group to CH-OH of raloxifene HCl, and degradation product B (m/z 462) was formed by opening of piperidine ring and dehydrogenation reaction of degradation product A as shown in Fig Results from force degradation studies are presented in Table Table Results of raloxifene exposed to different degradative pathways Stress condition Retention time % Assay USP tailing Major degradation Remark No Degradation (control) products _ No degradation Oxidation (20% H 2 O 2 ) Reduction ( Zn in 1 N HCl at 60 ºC for 1 h) Alkaline (1 N NaOH at 60 ºC for 8 h) Acid (1 N HCl at 60 ºC for 8 h) UV (254 nm for 8 h) Water hydrolysis (60 ºC) _ No degradation Degradation product A (80.85%) Degradation product B (6.79%) Degradation products were eluted separately No degradation _ No degradation _ No degradation _ No degradation Department of Pharmaceutics 107 Jamia Hamdard

19 Fig UPLC Chromatogram of raloxifene HCl stressed samples with their blank: (from top to bottom) oxidative degradation, reductive degradation, alkaline degradation, acid degradation, photolytic degradation and water hydrolysis Department of Pharmaceutics 108 Jamia Hamdard

20 Fig Structures of degradation product formed during reductive stress study Assay of raloxifene HCl in nanoparticulate formulation The developed method is sensitive and has been applied for the estimation of drug in nanoparticulate formulation. Nanoparticulate formulation was evaluated for the amount of raloxifene HCl present. Each sample was analyzed in triplicate after extracting the drug as mentioned in section The amount of raloxifene HCl in nanoparticulate formulation was % with a % RSD of None of the nanoparticulate formulation ingredient interfered with analyte peak. The developed and validated UPLC method was found to be simple, rapid, efficient, and stability-indicating which efficiently separated degradation impurities formed during forced degradation studies from analyte peak. Satisfactory results were obtained from validation of the method. The present method offers several advantages such as wider concentration Department of Pharmaceutics 109 Jamia Hamdard

21 range, lower reagent consumption and excellent performance in terms of speed and sensitivity. This method can be used for routine analysis of production samples and to check the stability of samples of raloxifene HCl Liquid chromatography-mass spectrometry (LC-MS/MS) Method for the analysis of raloxifene HCl in biological samples Method Development The mass spectrometric conditions were optimized to obtain maximum sensitivity. Raloxifene can be ionized under either positive (ESI+) or negative (ESI-) electrospray ionization conditions. However, the ESI in positive ion mode was adopted for the LC- MS/MS determination of raloxifene HCl because a higher sensitivity was achieved in the ESI+ than in the ESI- mode. The typical SIM spectrum of raloxifene HCl is shown in Fig The major product ion included m/z to 68.84, 84.8, , for raloxifene and m/z to 74.00, for IS. In order to enhance and stabilize the response, ammonium formate was added in the mobile phase. In this study, the good separation of target compounds was obtained with a mobile phase of the mixture of solvent A (10 mm ammonium formate with 0.1% formic acid in water) and solvent B (acetonitrile). Under the present chromatographic conditions, the retention time of raloxifene and IS was about 1.57 and 2.40 min, respectively. For rat plasma samples at each batch, the regions of the analyte and IS were found to be free of interference. RALOXIFENE-MSMS (0.473) Cm (10:81) Daughters of 475ES+ 1.50e6 % Fig Positive ion product-ion scan spectra recorded from raloxifene; samples diluted at 1 µg/ml were infused at 10 µl/min m/z Department of Pharmaceutics 110 Jamia Hamdard

22 Method Validation Linearity The assay was linear over the range ng/ml for raloxifene HCl. The standard curve fitted to a 1/c weighed linear regression which was calculated by the quantitative module of Mass Lynx software. The mean equation (curve coefficients± S.D.) of the calibration curve (n=8) obtained from three single batches in method validation was y = (± ) x (± ) for raloxifene HCl, where y represents the raloxifene HCl peak area to bisoprolol peak area ratio and x represents the plasma concentration of the raloxifene HCl. Good linearity (r 2 = ± 0.012) was observed in the concentration ranges of ng/ml. The lower limit of the quantification was 5 ng/ml for raloxifene HCl in rat plasma Precision and accuracy Satisfactory results were found and the results are summarized in Table for intra and inter-day precision and accuracy of the raloxifene HCl assay. Table Precision and accuracy of the method as measured by the performance of samples analyzed on three different days at four concentrations Concentration Amount found Precision Accuracy (%) (ng/ml) (ng/ml) (%RSD) Intra-day Inter-day *Each mean value is the result of six replicate analysis Selectivity There was no significant interference or ion suppression from endogenous substances observed at the retention times of analyte i.e., 1.57 and 2.40 min for raloxifene HCl and bisoprolol respectively. HPLC traces for the MRM transition chromatograms of blank plasma (Fig ), plasma spiked with raloxifene and internal standard (Fig ) were compared to show the selectivity of the proposed procedure. Department of Pharmaceutics 111 Jamia Hamdard

23 BLANK MRM of 6 Channels ES > MRM of 6 Channels ES TIC e % % Fig HPLC traces for the MRM transition selected for raloxifene HCl (top chromatograms) and bisoprolol (IS) (bottom chromatograms) recorded on a blank plasma Time Extraction Recovery The extraction recoveries and standard deviation were 82 ± 5.5%, 86 ± 4.8%, 90 ± 5.3% and 89 ± 2.5 % for 5, 15, 200 and 1500 ng/ml raloxifene HCl respectively and 85 ± 7.5% for the internal standard. These results indicated that the sample procedure of protein precipitation with acetonitrile was efficient for the extraction of traces raloxifene in plasma. The assay has been proven to be robust in high throughput bio analysis. CAL Sm (Mn, 1x1) 3: MRM of 7 Channels ES Sum 4.67e : MRM of 7 Channels ES Sum 1.02e6 85 % % Fig HPLC traces for the MRM transition selected for raloxifene HCl (top chromatograms) and bisoprolol (IS) (bottom chromatograms) recorded on a plasma spiked with raloxifene for CAL 8 (2 µg/ml) Time Department of Pharmaceutics 112 Jamia Hamdard

24 Stability The result obtained by stability study indicated that the processed samples were stable at room temperature for at least 24 h. Similarly, the QC samples spiked plasma were analyzed at fresh preparing and stored at -20 ºC, then subjected to three freeze and thaw (12 h) cycles to investigate freeze and thaw stability. The concentrations found were within the allowed limit ± 15% of nominal concentrations, revealing no significant substance loss during repeated freezing and thawing. The plasma samples remained stable after freezing and thawing for at least three times. Plasma samples were also stable at room temperature for at least 24 h and at -20 ºC for at least 8 weeks FORMULATION, OPTIMIZATION AND EVALUATION OF CHITOSAN NANOPARTICULATE FORMULATION Preparation and optimization of PLGA nanoparticles and chitosan coated PLGA nanoparticles The raloxifene loaded PLGA nanoparticulate formulations were prepared as given in section The prepared formulations of raloxifene loaded PLGA nanoparticulate suspensions as shown in Table 5.13., were analyzed for particle size, polydispersity index (PDI), drug entrapment efficiency and drug loading. Table Particle size, PDI, entrapment efficiency and loading efficiency of various formulations of PLGA nanoparticles (n=3) Mean % Entrapment % Drug Formulation Drug : particle size PDI ± SD Efficiency ± SD Loading ± Code Polymer (nm) ± SD (n=3) (n=3) SD (n=3) (n=3) A1 1: ± ± ± ±4.06 A2 1: ± ± ± ±3.03 A3 1: ± ± ± ±2.04 A4 1: ± ± ± ± 2.05 Major limitations in the application of PLGA nanoparticles for intranasal drug delivery are their negative charge, which limits the interaction with the mucin and other cellular components and poor transport characteristics of the PLGA nanoparticles through the cell Department of Pharmaceutics 113 Jamia Hamdard

25 membrane. Therefore, to overcome this attempts have been made to modify the surface of PLGA-NP using cationic polymers e.g. chitosan (Kim et al., 2008). The raloxifene loaded chitosan coated PLGA nanoparticulate formulations were prepared as given in section The prepared formulations of raloxifene loaded chitosan coated PLGA nanoparticulate suspensions as shown in Table 5.14., were analyzed for particle size, polydispersity index (PDI), drug entrapment efficiency and drug loading. Table Particle size, PDI, entrapment efficiency and loading efficiency of various formulations of chitosan coated PLGA nanoparticles (n=3) Mean particle % Entrapment % Drug Formulation Drug : PDI ± size (nm) ± Efficiency ± SD Loading ± Code Polymer SD (n=3) SD (n=3) (n=3) SD (n=3) A1 1: ± ± ± ± A2 1: ± ± ± ± A3 1: ± ± ± ± A4 1: ± ± ± ± 1.95 Since chitosan coated PLGA nanoparticles had greater particle size with poor entrapment and loading efficiency, therefore, chitosan nanoparticles were planned in order to achieve objectives of the present study Formulation Development of chitosan nanoparticles (CS NPs) by ionic gelation method Preparation of placebo chitosan nanoparticles The chitosan nanoparticles were prepared by ionic gelation method as mentioned in section The placebo chitosan nanoparticles were prepared in different batches. The visual observations of the formulations were recorded and are given in Table Department of Pharmaceutics 114 Jamia Hamdard

26 Table Placebo chitosan nanoparticles were prepared in different batches Formulation code Concentration of CS (% w/v) Volume of CS (ml) Batch-I Concentration of TPP (% w/v) Volume of TPP (ml) Visual observation F1 1 Clear F2 2 Clear F Clear F4 4 Clear F5 5 Opalescent Formulation code Concentration of CS (% w/v) Volume of CS (ml) Batch-II Concentration of TPP (% w/v) Volume of TPP (ml) Visual observation F6 1 Clear F7 2 Clear F Opalescent F9 4 Precipitation F10 5 Precipitation Formulation code Concentration of CS (% w/v) Volume of CS (ml) Batch-III Concentration of TPP (% w/v) Volume of TPP (ml) Visual observation F11 1 Clear F12 2 Opalescent F Precipitation F14 4 Precipitation F15 5 Precipitation Formulation code Concentration of CS (% w/v) Volume of CS (ml) Batch-IV Concentration of TPP (% w/v) Volume of TPP (ml) Visual observation F16 1 Clear F17 2 Opalescent F Precipitation F19 4 Precipitation F20 5 Precipitation Department of Pharmaceutics 115 Jamia Hamdard

27 Table The particle size, PDI and process yield of various formulations optimized after visual observation (n=3) F. Final Conc. of Final Conc. chitosan Mean Mean code chitosan of TPP /TPP particle size PDI± S.D ratio (nm) ± (S.D) F ± ±0.01 F ± ±0.02 F ± ±0.03 F ± ±0.03 The placebo chitosan nanoparticles were prepared in different batches and visual observations were recorded as shown in Table All the preparations were visually analyzed and three different systems were identified: clear solution, opalescent suspension and precipitates. The appearance of opalescent suspension corresponds to a suspension of very small particles. The appearance of these formulations was also observed microscopically and samples were classified as precipitates, suspension and clear solution. Nanoparticles are formed immediately upon mixing of TPP and chitosan solutions as molecular linkages were formed between TPP phosphates and chitosan amino groups. Chitosan in acidic media (pka 6.5) can interact with the negatively charged TPP, forming inter- and intra molecular crosslinkages, yielding ionically crosslinked chitosan nanoparticles (De Campos et al., 2001; Dumitriu & Chornet, 1998; Wong et al., 1999; Xu & Du, 2003). This method results in spontaneous formation of nanoparticles of smaller size with positive charge (De Campos et al., 2001; Pan et al., 2002) without using any organic solvent or surfactants at surfaces (Hu et al., 2002). The four formulations were selected from different batches from Table 5.15 and these formulations were observed for particle size and PDI as shown in Table These formulations were further characterized on the basis of entrapment efficiency Preparation of drug loaded chitosan nanoparticles The drug loaded chitosan nanoparticles were prepared and recorded as shown in Table The drug loaded chitosan nanoparticles were optimized on the basis of particle size, PDI, and entrapment efficiency (EE %) Department of Pharmaceutics 116 Jamia Hamdard

28 Table The particle size, PDI and entrapment efficiency (EE %) of various drug loaded formulations were optimized after placebo formulation (n=3). Mean Conc. of Drug F. chitosan particle size PDI ± (S.D) EE (%)± chitosan Conc.mg code /TPP (nm) ± (n=3) (S.D) (n=3) (%w/v) /ml (S.D) (n=3) F ± ± F ± ± F ± ± F ± ± It was obvious from Table 5.17 that the incorporation of drugs into chitosan nanoparticles leads to a drug proportion-dependent increase of their size (hydrodynamic diameter) compared with the placebo nanoparticles. This was in agreement with previously reported data (Gan et al., 2005; Hu et al., 2008). Entrapment efficiency (EE) is defined as percentage of raloxifene loading content that can be entrapped into chitosan /TPP nanoparticles. Maximum entrapment of drug was observed in F17 formulation. Therefore, this formulation was selected for determining the effect of drug concentration on particle size, PDI and EE%. Effect of drug concentration on particle size, PDI and EE% The effects of drug concentration on particle size, PDI and EE of raloxifene loaded chitosan /TPP nanoparticles are summarized in Table On increasing the drug concentration from 0.2 to 0.8 mg/ml, the average size of chitosan /raloxifene nanoparticles was increased from 180 ± 9.52 to 300 ± nm showing a positive linear correlation between drug concentration and mean particles size as showed in Fig (R 2 = 0.968). The increase in drug concentration also slightly increased the PDI value. Table Optimization of drug loading concentration on particle size, PDI, and EE of drug loaded chitosan nanoparticles (n=3) Drug conc. (mg/ml) Mean particle size (nm) ± (S.D) Mean PDI± S.D Entrapment Efficiency ± S.D ± ± ± ± ± ± ± ± ± ± ± ± 3.76 Department of Pharmaceutics 117 Jamia Hamdard

29 Fig Effect of drug concentration on particle size of raloxifene loaded chitosan nanoparticles, (chitosan concentration (%w/v) and CS/TPP mass ratio 2.00/1) Increasing drug proportion caused an increasing reduction of CS/TPP interaction, which leads to increase in nanoparticles size. Initial increase in concentration of raloxifene HCl increases the EE from 30 ± 4.76 to 76 ± 6.65 due to more cross linking site of CS which interact with the raloxifene HCl. Decrease of EE from 76 ± 6.65 to 49 ± 3.76% was observed when loading concentration of raloxifene HCl was increased from 0.4 to 0.8 mg/ml. As the raloxifene HCl loading concentration increased, more raloxifene HCl molecules were just electrostatically adsorbed onto the surface of CS and were easily separated from CS nanoparticles by centrifugation. The decrease in entrapment may also be due to saturation kinetics which reaches a peak value of entrapment at high concentration of raloxifene HCl after that downfall occurs. These findings were in agreement with studies carried out by (Berthold et al., 1996) showing the entrapment of prednisolone as a model for anti-inflammatory drugs. This formulation was further optimized using Design expert. Four independent parameters were considered to optimize the formulation. These parameters were chitosan concentration, TPP concentration, stirring speed and TPP ph. Department of Pharmaceutics 118 Jamia Hamdard

30 Optimization of raloxifene loaded chitosan nanoparticles by using central composite design The chitosan nanoparticles were prepared by ionic gelation method as mentioned in section Table Results of central composite design for chitosan nanoparticulate formulation Code value Actual value S.No. Chitosan conc % w/v TPP conc % rpm TPP ph Particle size ± SD (n=3) Entrapment efficiency ± SD (n=3) Loading efficiency± SD (n=3) w/v ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± 3.83 The raloxifene loaded-nanoparticulate suspensions were analyzed for mean particle size (R1), drug entrapment efficiency (R2), and drug loading (R3) as shown in Table All the results were placed in central composite design of Design Expert 8.1 software. There were total 30 runs for optimizing the raloxifene-nanoparticulate formulation as shown in Table Department of Pharmaceutics 119 Jamia Hamdard

31 Effect of independent factors on particle size The effect of particle size response was determined, as shown in Table The model proposed the following polynomial equation for particle size: R1 = A B C D AB BD CD A B C D 2 Where, R1 is the particle size of nanoparticles, A is chitosan concentration, B is TPP concentration, C is the stirring speed and D is the TPP ph. The model F-value of implied that the model was significant (p < ). The Lack of Fit F-value of 1.61 implied that the Lack of Fit is not significant (p = ). B Fig Contour plots and response surface plots for particle size showing effects of independent factors Department of Pharmaceutics 120 Jamia Hamdard

32 Contour plot for determining particle size using chitosan concentration and TPP concentration as variables; A1: Response surface plot for determining particle size using variables as chitosan concentration and TPP concentration; B: Contour plot for determining particle size using TPP concentration and TPP ph as variables; B1: Response surface plot for determining particle size using variables as TPP concentration and TPP ph; C: Contour plot for determining particle size using stirring speed and TPP ph as variables; C1: Response surface plot for determining particle size using variables as stirring speed and TPP ph. In this case A, B, C, D, AB, BD, CD, A 2, B 2, C 2 and D 2 are significant model terms. The "Pred R- Squared" of was in reasonable agreement with the "Adj R-Squared" of The Adeq Precision of indicated an adequate signal. Therefore this model was used to navigate the design space. The contour and response surface plots for particle size are shown in Fig The actual and predicted values for particle size are given in Table 5.20 and a plot of predicted vs. actual values is shown in Fig Fig Plot of predicted versus actual values for particle size Department of Pharmaceutics 121 Jamia Hamdard

33 Table Actual and predicted values for particle size Formulation Actual Value Predicted F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± Department of Pharmaceutics 122 Jamia Hamdard

34 Effect of independent factors on drug entrapment efficiency The prepared formulations analyzed showed effect on the drug entrapment efficiency as reported in Table Fig Contour plots and response surface plots for percent drug entrapment showing effects of independent factors Department of Pharmaceutics 123 Jamia Hamdard

35 A: Contour plot for percent drug entrapment using TPP concentration and chitosan concentration as variables; A1: Response surface plot for percent drug entrapment using variables as TPP concentration and chitosan concentration; B: Contour plot for determining percent drug entrapment using stirring speed and chitosan concentration as variables ; B1: Response surface plot for determining percent drug entrapment using variables as stirring speed and chitosan concentration; C : Contour plot for determining percent drug entrapment using variables as stirring speed and TPP concentration; C1: Response surface plot for determining percent drug entrapment using stirring speed and TPP concentration as variables. The model proposed the following polynomial equation for percentage drug entrapment: R2 = A B C AB AC BC A B D 2 Where, R2 is the drug entrapment efficiency of nanoparticles, A is chitosan concentration, B is TPP concentration, C is the stirring speed and D is the TPP ph. The model F-value of implied that the model was significant (p < ). The Lack of Fit F- value of 3.13 implied that the Lack of Fit is not significant (p = ). In this case A, B, C, AB, AC, BC, A 2, B 2, D 2 were the significant model terms. The "Pred R-Squared" of was in reasonable agreement with the "Adj R-Squared" of The Adeq Precision of indicated an adequate signal. Therefore this model was used to navigate the design. The contour and response plot of percent drug entrapment are shown in Fig The actual and predicted values for drug entrapment efficiencies are given in Table 5.21.and a plot of predicted vs. actual values is shown in Fig Fig Plot of predicted vs. actual values for percentage on drug entrapment Department of Pharmaceutics 124 Jamia Hamdard

36 Table Actual and predicted values for entrapment efficiency Formulation Actual Value Predicted F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± Department of Pharmaceutics 125 Jamia Hamdard

37 Effect of independent factors on drug loading Drug loading was another response determined, as shown in Table The model proposed the following polynomial equation for drug loading: R3 = A B C AB AC BC BD A B D 2 Where, R3 is the drug loading of nanoparticles, A is chitosan concentration, B is TPP concentration, C is the stirring speed and D is the TPP ph. The model F-value of implied that the model was significant (p < ). The Lack of Fit F-value of 2.39 implied that the Lack of Fit was not significant (p = ). In this case A, B, C, AB, AC, BC, BD, A 2, B 2 and D 2 are significant model term. The "Pred R-Squared" of was in reasonable agreement with the "Adj R-Squared" of The Adeq Precision of indicated an adequate signal. Therefore this model was used to navigate the design space. The contour and response surface plots for percent drug loading are shown in Fig Department of Pharmaceutics 126 Jamia Hamdard

38 Fig Contour plots and response surface plots for percent drug loading showing effects of independent factors Department of Pharmaceutics 127 Jamia Hamdard

39 A: Contour plot for determining percent drug loading using TPP concentration and chitosan concentration as variables; A1: Response surface plot for determining percent drug loading using TPP concentration and chitosan concentration as variables; B: Contour plot for determining percent drug loading using stirring speed and chitosan concentration as variables; B1: Response surface plot for determining percent drug loading using stirring speed and chitosan concentration as variables; C: Contour plot for determining percent drug loading using variables as stirring speed and TPP concentration; C1: Response surface plot for determining percent drug loading using stirring speed and TPP concentration as variables; D: Contour plot for determining percent drug loading using stirring speed and TPP concentration as variables; D1: Response surface plot for determining percent drug loading using TPP ph and TPP concentration as variables. The actual and predicted values for drug loading are given in Table 5.22 and a plot of predicted vs. actual values is shown in Fig Fig Plot of predicted vs. actual values for percentage drug loading Department of Pharmaceutics 128 Jamia Hamdard

40 Table Actual and predicted values for drug loading Formulation Actual Value Predicted Value F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± F ± Department of Pharmaceutics 129 Jamia Hamdard

41 Optimized formula The results of the 30 formulations prepared using the experimental design criteria followed for generating the optimized formula are based on selecting the individual variable and defining their goal and limits. Table 5.23 gives the optimization constraints selected for each variable. After defining the constraints for each variable, the Design Expert software automatically generated the optimized formula. Table 5.24 gives the optimized formula generated by design expert software showing the predicted and experimental values. Sufficient replicates of nanoparticles were prepared based on the optimized formula and then the characterization studies were carried out. The optimized formula was determined after studying the effects of the independent variables. Table Optimized constraints selected for each variable Variables Constraints Lower limit Upper limit Goal Independent variables A = Chitosan conc. (%) In range B = TPP conc. (%) Equal to C = Stirring speed (rpm) In range D = TPP ph In range Dependent variables R1 = Particle size (nm) Minimize R2 = Entrapment efficiency (%) Maximize R3 = Drug loading (%) Maximize Table Predicted and experimental values obtained based on optimized formula generated by Design Expert software Predicted values based on optimized formula Chitosan conc. (%) Independent factors TPP Stirring conc. speed (%) (rpm)) Dependent factors Drug Particle size Entrapment TPP ph loading (nm) efficiency (%) (%) Chitosan conc. (%) Experimental values based on optimized formula Independent factors Dependent factors TPP Stirring Particle size Entrapment conc. speed TPP ph (nm) efficiency (%) (%) (rpm)) Drug loading (%) ± ± ± Percentage of prediction error Department of Pharmaceutics 130 Jamia Hamdard

42 In vitro release studies for raloxifene loaded chitosan nanoparticulate suspension The comparative in vitro release study was performed as mentioned in section to observe the release pattern of drug suspension with drug loaded nanoparticulate suspension and the result are shown in Table and Fig Table In vitro release data of drug suspension and optimized nanoparticulate formulation Time (min) Cumulative % drug released from Drug suspension. n=3 (± SD) Cumulative % drug released from Drug loaded nanoparticulate n=3 (± SD) ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±0.55 In vitro studies were carried out with optimized formulation for their in vitro studies release pattern across dialysis membrane. Initial release of the drug is associated with those drug molecules dispersing close to the nanoparticles surface. Fig In vitro release profile of raloxifene HCl suspension and raloxifene HCl nanoparticulate formulation (n=3) Department of Pharmaceutics 131 Jamia Hamdard

43 Raloxifene loaded chitosan nanoparticles showed much faster in vitro dissolution rate than raloxifene drug suspension. Within 1 h, approximately 75% of drug was released in to the dissolution medium from nanoparticulate system and more 90% of drug was released within 2 h while drug suspension showed less than 60% release even after 2 h. This improvement in dissolution rate of drug from nanoparticulate system was because of dissolution rate enhancer property of chitosan which was earlier reported by Sawanagi et al., 1983, Genta et al., 1995) and also can be due to their small size. The two-tailed t-test showed statistically significant differences (p< ) between the release behavior of nanoparticulate system and drug suspension Establishment of mechanism of drug release The penetration behaviour of carrier chitosan nanoparticles in nasal mucosa is already established and reported in various literatures. There are various methods to evaluate the penetration behavior of carrier chitosan nanoparticles such as investigations in cell culture (CaCo-2). The penetration behaviour of carrier chitosan nanoparticles in nasal mucosa is due to the absorption promoting effect of chitosan (Artursson et al., 1994). Chitosan is mucoadhesive in nature and improves adhesion with the nasal mucosa. Chitosan also has a transient effect on paracellular transport processes (Dodane et al., 1999). The mucoadhesive CS-NPs can adhere and penetrate into the mucus layer in the nasal epithelium. Subsequently, the penetrated NPs transiently open the tight junctions between epithelial cells while becoming unstable and disintegrated, due to their ph-sensitivity, to release the loaded drug. The released drug then permeates through the opened paracellular pathway and enters into the bloodstream. Investigations in cell culture (CaCo-2) as well as in animal models have also demonstrated that chitosan can have an effect in modifying paracellular transport. This combination of bioadhesion and paracellular transport effects has led to a consideration of the use of chitosan for the delivery of nanoparticles via the nasal cavity. Sonaje and coworkers demonstrated that the orally administered NPs were able to adhere and infiltrate into the mucus layer of the intestinal tract. The infiltrated NPs subsequently mediated the transient opening of the tight junctions between epithelial cells while destabilizing and disintegrating due to their ph sensitivity. The insulin released from the disintegrated NPs was then able to diffuse through the opened paracellular pathway to the systemic circulation, leading to a significant improvement in its bioavailability (Sonaje et al., 2009). Mathematical models were applied to study the release kinetics from the nanoparticulate formulation. The mathematical models used along with the results obtained are given in Table There are several models to represent the drug dissolution profiles. The quantitative interpretation of kinetics of drug release from the values obtained in dissolution profile is facilitated by the usage of equations that mathematically translates the dissolution data. Department of Pharmaceutics 132 Jamia Hamdard

44 Various mathematical models were applied to the release profiles of the optimized nanoparticulate suspension formulation as shown in Table The plots obtained for each of the mathematical model are shown in Fig From the values of correlation coefficient obtained, it was found that the drug release from optimized nanoparticulate formation followed Higuchi release kinetics. The release kinetics had the maximum R 2 value of for Higuchi model. Thus it followed Higuchi model which is an indicative of diffusion mechanism of drug release. Fickian diffusional release occurs by the usual molecular diffusion of the drug due to a chemical potential gradient (Cox et al., 1999). Table Mathematical models used along with their equations and values for the optimized formulation Zero order First order Higuchi Nanoparticulate r 2 K o (h -1 ) r 2 K 1 (h -1 ) R 2 K H (h -1/2 ) formulation Fig Plots of the mathematical models used for the evaluation of drug release kinetics from the optimized formulation; A-Zero order kinetics; B-First order kinetics; C-Higuchi Model Characterization of the optimized raloxifene HCl loaded chitosan formulation The optimized nanoparticulate formulation was analyzed by various characterization techniques as follows: Department of Pharmaceutics 133 Jamia Hamdard

45 Morphology and shape: Morphological studies showed raloxifene HCl loaded chitosan nanoparticles were spherical with smooth surfaces TEM for particle size Particle size was determined as mentioned in section The representative TEM photomicrographs for the optimized formulation of raloxifene HCl is shown in Fig The photomicrograph of the formulation suggested the range of particle size of nm. Fig TEM photomicrograph of optimized chitosan nanoparticulate formulation SEM for surface studies The SEM was analyzed as mentioned in section The optimized nanoparticulate formulation was found to be spherical in shape and had rough morphology. The SEM photomicrograph for the optimized formulation of raloxifene HCl is shown in Fig Fig SEM photomicrograph of optimized chitosan nanoparticulate formulation Department of Pharmaceutics 134 Jamia Hamdard