1,2,3,4, Channabasweshwar College (Degree) Latur - 413512 , Maharashtra, India
5 Department of Chemical Engineering Hanseo University, Hanseo-2gil, Haemi-myun, Seosan-si, South Korea
Poor solubility, erratic bioavailability and delivery challenges associated with gliclazide, can be overcome by exploring electrospun nanofibers technology using a Quality by design (QbD) approach. Using a design of experiment, factors influencing the % drug release were investigated. Polymer concentration, applied voltage, and flow rate are the parameters examined. Polymer concentration was shown to be the only statistically significant factor within the ranges studied (p-value = 0.0042). The optimized processing conditions identified were a applied voltage of 19 kV, with a flow rate of 0.05 mL/min. Using this knowledge, the production optimization of electrospun PMMA & PVPK90 polymer with gliclazide, a antidiabetic drug, was explored. Employing solution-based electrospinning method with (PVPK90) alone and in combination with (PMMA), nanofibers were fabricated. Fabricated gliclazide-nanofibers were characterized by various studies, such as solubility, in-vitro drug release, scanning electron microscopy (SEM), differential scanning calorimetric (DSC), and Fourier transform infrared (FTIR) spectroscopy. MDPF, formulation of PMMA: PVPK90: GLC (7:3:15% w/v) produced optimized gliclazide nanofibers.
One of the most simple and sophisticated methods in nanotechnology is electrospun fiber production, which has great potential as a drug carrier for therapeutic delivery. Drug carriers are created using polymeric electrospun fibers with diameters ranging from several nanometers to several micrometers by using polymer solutions under the influence of an electrostatic field [1]. The development of polymeric nanofiber as a specialized carrier system for the delivery of different therapeutics is a good idea because of its unique properties, such as high porosity, high surface area, high drug loading capacity, and increased drug release modulation flexibility. Nanotechnology-based fabricated nanofibers are being thoroughly studied for a range of uses, including wound dressing, surgical intervention, medication administration, gene transfer, catalysts, and sensors. [2]. A common second-generation sulphonylurea used to treat Type 2 Diabetes Mellitus is gliclazide. It increases insulin sensitivity and encourages the pancreatic beta cells to produce more insulin. Gliclazide is a class II medication according to the Biopharmaceutical Classification Systems (BCS), meaning it has strong membrane permeability and lipophilicity but low solubility. Gliclazide's poor solubility and slow rate of breakdown lead to uneven gastrointestinal absorption after oral dosing, which in turn produces unpredictable bioavailability. [3] Therefore, a polymeric nanofiber tailored carrier system for oral administration of gliclazide was investigated in this work in order to improve the drug delivery problems and therapeutic efficiency of gliclazide in type 2 diabetic mellitus (T2DM). Furthermore, numerous dosage was necessary for long-term therapeutic management of type 2 diabetes with standard formulation in order to maintain fasting and postprandial plasma glucose levels. The need to create a delivery mechanism that satisfies the physiological requirements of type 2 diabetes is great. In T2DM, the customized oral delivery method is crucial because it increases patient compliance and adjusts medication release based on plasma glucose requirements [3,4]. A few studies found that gliclazide's solubility, rate of dissolution, and ability to produce prolonged release of the medication were all enhanced when it was incorporated into polymer matrices such solid dispersion and nanocrystal formulation. Nevertheless, the method of electrospinning Polymethyl methacrylate (PMMA) and Polyvinylpyrrolidone (PVP-K90) polymers to create electrostatic fiber, which serves as a vehicle for gliclazide administration, has not been documented or investigated. Gliclazide-loaded PMMA / PVP-K90 electrostatic fibers were created in this study using the electrospinning technique to address the issues associated with drug delivery by improving drug dissolution and changing the drug release profile. Gliclazide nanofibers were created by electrospinning technique using polymethyl methacrylate (PMMA) alone and in conjunction with polyvinylpyrrolidone (PVP-K90) as core polymers. PMMA and PVP-K90 are synthetic, biocompatible polymers that are utilized as the primary polymer for nanofiber manufacturing and have been approved by the US Food and therapeutic Administration for use in therapeutic product development. Additionally, PVP-K90 was used as a secondary polymer to control the release of medication from PMMA nanofibers loaded with gliclazide. PVP-K90 is a biocompatible polymer that has been widely used in numerous documented therapies to achieve sustained drug delivery over an extended period of time [5,6,7] A modified drug release profile, such as a faster drug release during meals followed by a prolonged drug release profile over an extended period of time to maintain constant plasma glucose level, was achieved in this study by adding concentrations of PVP-K90 at 16% w/v to PMMA. This is highly desirable for better management of type 2 diabetes [8]. We have designed, produced, and characterized gliclazide-loaded PMMA / PVP-K90 electrospun nanofibers in this study as possible carriers to enhance gliclazide oral medication administration in Type-2 Diabetes. For oral delivery, an empty gelatine capsule containing the optimized gliclazide-loaded nanofiber formulation was added [9]. The gliclazide-loaded PMMA / PVP-K90 nanofibers were characterized morphologically and physicochemically. Differential scanning calorimetric (DSC), Fourier transform infrared (FTIR) spectroscopy, scanning electron microscopy (SEM), in vitro drug release, kinetics of drug release, and solubility studies were all conducted on the synthesized gliclazide nanofibers and were thoroughly discussed [10-13]. The DoE in this study was used to most influential factors for fabricating nanofibers. Smooth The factors chosen to be controlled represent the critical material attributes (CMAs) and were polymer concentration. The critical process parameters (CPPs) explored were flow rate and applied voltage.
Fig No: 1
METHODS
2.1. Materials
Gliclazide and PMMA were purchased from Hi Media Laboratories Pvt. Ltd. PVPK90 (Polyvinyl Pyrrolidione K-90) was purchased from RESEARCH-LAB FINE CHEM INDUSTRIES Mumbai 400002 (INDIA) (MW 360000). All other chemicals and reagents used in this research work were of analytical grade.
|
|
|
|
|
Gliclazide |
Poly(methyl methacrylate) [PMMA] |
Polyvinyl pyrrolidone K90 [PVPK90] |
2.2. Preparation of Spinning Solution for Gliclazide Electrospun Nanofibers
Polymer PMMA and PVPK90 was dissolved in DMF and Ethanol to form 10% (w/v) solution. The polymeric PMMA and PVPK90 mixture was then stirred for 4 h at room temperature. Then, gliclazide, 15% w/v to dry polymers in concentration 16% (7:3 ratio), were pre-dissolved in 10 ml of DMF and Ethanol. The mixture was then stirred for at least 20 min at room temperature to form homogenous solution before performing the electrospinning process. The design of different batches of formulations and their compositions used in the preparation of the spinning solution for gliclazide loaded PMMA/PVPK90 electrospun nanofibers. [6]
Table 1. Design of different batches of formulations and their composition used in gliclazide loaded PMMA (polymethyl methacrylate) & PVPK90 (Polyvinylpyrrolidone K 90) electrospun nanofibers
|
Formulation Code |
% w/v |
Nanofiber Fabrication Parameters |
||||||
|
|
Gliclazide |
PMMA |
PVPK90 |
Needle (I.D) |
Flow Rate in |
Voltage Applied |
Distance between Needle’s Tip and Collector |
Ambient Condition |
|
M1 (Blank PMMA Nanofiber) |
0 |
10 |
0 |
1.8 |
0.05 |
19 |
9 |
RT |
|
M2 |
00 |
9 |
1 |
1.8 |
0.05 |
19 |
9 |
RT |
|
M3 |
0 |
8 |
2 |
1.8 |
0.05 |
19 |
9 |
RT |
|
M4 |
(15%) |
7 |
3 |
1.8 |
0.05 |
19 |
9 |
RT |
|
M5 |
0 |
6 |
4 |
1.8 |
0.05 |
19 |
9 |
RT |
|
M6 |
0 |
5 |
5 |
1.8 |
0.05 |
19 |
9 |
RT |
|
M7 |
0 |
4 |
6 |
1.8 |
0.05 |
19 |
9 |
RT |
|
M8 |
0 |
3 |
7 |
1.8 |
0.05 |
19 |
9 |
RT |
|
M9 |
0 |
2 |
8 |
1.8 |
0.05 |
19 |
9 |
RT |
|
M10 |
0 |
1 |
9 |
1.8 |
0.05 |
19 |
9 |
RT |
|
M11 |
0 |
0 |
10 |
1.8 |
0.05 |
19 |
9 |
RT |
2.3. Electrospinning Process
The prepared solution was transferred into a 2 ml plastic syringe fitted with a metallic needle (24Ga 1 Inch). During the electrospinning process, the distance between the needle and the collector was maintained at 15cm while the applied voltage was set at 19 kV. The flow rate was adjusted to 0.05 µL/min for all runs. Nanofibers were produced using the ESpin machine and collected on a grounded aluminum drum covered with aluminum foil paper.
Figure No 2: Schematic representation for preparation of GLC-loaded electrospun nanofibers mat.
2.4. Characterizations of Gliclazide Nanofibers
2.4.1. Drug Content Study
Nanofiber was dissolved in the same composition of solvents used for spinning and suitably diluted to get gliclazide 10 µg/ml in the final concentration and UV spectrum was taken using UV spectrophotometer (Shimadzu UV-1800). The solution was scanned in range of 200-400 nm [3].
2.4.2. Calibration Curve using UV-Vis Spectrophotometer
50 mg of gliclazide was accurately weighed and dissolved in 100ml volumetric flask and then make up the volume upto 100 ml by using spinning solution (7:3) from that solution pipette out 1ml in 10ml volumetric flask and make up the volume to get 50 µg/ml concentration solution. From that solution (1,2,3,4 & 5ml) pipette out and final volume was made upto 10 ml volumetric flask. To get final conc. of 5,10,15,20, and 25µg/ml and analyzed using the UV spectrophotometer by (Shimadzu UV1800), at 228 nm. [17]
2.4.3. Scanning Electron Microscopy (SEM) Studies
The surface morphology was determined using scanning electron microscope (JEOL JSM-6400). The samples were cut into circular shape with an average diameter of 1.5 cm. Specimens were coated with a thin gold layer using a sputter. The diameters were measured using a SemAphore 4.0 software at 5000_magnification. More than 50 individual fibers were measured for their diameters and reported as mean ± SD. Different parts of each nanofiber sample was selected for measurement and the average fiber diameter was calculated [14].
2.4.4. FTIR
FT-IR of blank nanofibers PMMA/ PVPK90 and drug-loaded PMMA/ PVPK90/Gliclazide was performed for analysing the compatibility between pure drug, polymer and combination of drug-polymer. Each sample was scanned over a wavenumber region of 4000-400 cm-1 and typical bands were noted shows in figure no.8,9,10. [3,14].
2.4.5. Differential Scanning Calorimeter (DSC)
DSC can determine the glass transition temperature (Tg), melting temperature (Tm), and crystallization temperature (Tc) of nanofibers. These thermal properties are crucial in understanding the stability and processing conditions of nanofibers.as shown in figure no.7
2.4.6. Entrapment Efficiency
The drug entrapment efficiency of nanofibers was measured by drying drug-enriched nanofibers in a hot air oven for 5 min at 41 °C, then the nanofibers scaffold of known area 1 cm2 was removed and dissolved it in water. The amount of drug loaded into these fibers was estimated by UV analysis. The Entrapment Efficiency was calculated by eq. 1.
Entrapment efficiency %=Mass of drug released/Mass of total drug added 100
2.4.7. In Vitro Drug Release Studies and Drug Release Kinetic Studies
The in vitro drug release studies were performed for pure gliclazide, nanofiber formulations, optimized formulation, and were determined by USP dissolution apparatus II. Electrospun nanofiber (equivalent to 100 mg gliclazide) was accurately weighed and the nanofibers sample was gently rolled over a glass carrier and inserted into the dissolution apparatus. The samples were then put into vessels containing 900 mL phosphate buffer (pH 7.4) under the stirring rate 100 rpm, maintained at 37 ± 0.5 °C. Aliquots of 1 ml were withdrawn at fixed time intervals (1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14 h) and replaced with fresh phosphate buffer solution. The sample solution was filtered with 0.45 µm and then analyzed using a UV-spectrophotometer by SHIMADZU UV 1800 with a wavelength of 228nm. [3,15,16].
2.4.8. Experimental Design
A DoE approach was utilized to optimize the electrospinning of nanofibers on its own using a definitive screening design. Definitive screening designs help to detect the main effects of input parameters on a particular outcome in the most efficient way possible Design Expert 9 (version 9.1.0.) was used for experimental design, predictive modeling, and data analysis. Smooth non beaded fibers, with a %drug release, were set as the desired output criteria. Three factors were investigated at three levels of each, as shown in Table no. 6.
RESULTS AND DISCUSSION
In the treatment of type 2 diabetes, numerous oral hypoglycemic medication doses and long-term medication have been standard procedures. Gliclazide is a clinically safe and licensed first-line medication that is frequently suggested in the therapy of type 2 diabetes. The main issues connected with this medication are frequent administration of oral hypoglycemic medications, adverse effects, and poor patient compliance. In patients with type 2 diabetes, conventional oral gliclazide dosage forms result in poor absorption, unpredictable therapeutic response, and a large dose that must be taken often. The usual physiological goal of type 2 diabetes (T2DM) was not met by a traditional oral gliclazide treatment. This includes meeting basic needs during the night and in between meals, which require a longer drug release profile followed by a faster drug release in order to maintain a constant plasma glucose level over an extended period of time. Gliclazide was delivered orally using an inventive functional polymeric electrospun nanofibers technique, which addressed the problems with drug delivery related to this method. This study's primary goal was to investigate the cutting-edge idea and technology of electrospun nanofibers in the creation, development, and administration of an oral gliclazide dosage form for the treatment of type 2 diabetes. As indicated in Table 1, gliclazide nanofibers were effectively fabricated using the solution electrospinning technique using PVPK90 as the functional polymer both alone and in conjunction with PMMA. In order to improve the management of type 2 diabetes, PVPK90 was treated with varying doses of PMMA (16% w/v). This resulted in a changed drug release profile. Table 2 displays the solubility of all gliclazide nanofiber formulations in comparison to pure gliclazide, along with the increase in solubility data. The form and appearance of PVPK90 nanofiber blanks and formulations loaded with gliclazide were examined using a scanning electron microscope (SEM), as illustrated in... The SEM studies are generally done to study surface morphology if the drug nanofiber. The photographs were studied for morphological characteristics. The surface morphology was determined using scanning electron microscope (JEOL JSM-6400). The samples were cut into circular shape with an average diameter of 1.5 cm. Specimens were coated with a thin gold layer using a sputter. The fiber diameters were measured using a SemAphore 4.0 software at 20000 magnifications as shows as.
Figure No 3. Scanning electron microscopy (SEM) images of gliclazide nanofibers & (PVPK90) nanofibers.
Morphological properties of the GLC/PMMA Electrospun NF were investigated by SEM. In case of drug it exhibited a crystalline morphology with crystal structure. In case of plain polymer, it shows a amorphous structure. The nanofiber with plain PMMA resulted with broken fiber morphology. While it mixed with PVPK90 it starts to give continuous fiber but while increasing the PVP K-90 the fibers exhibit morphology with beads and twisted morphology. Hence, the formulation with 7:3 was selected for further drug loading and evaluation. While in case of drug loaded formulation the fibers resulted with minimum beads with neat fiber morphology.
X ray diffraction studies (XRD)
To understand the crystallinity of the drug in the nanofiber membrane, XRD pattern of pure drug, CPD and their optimized MDPF membrane were recorded. The XRD pattern of GLC, as shown in Figure no. 4, exhibited four characteristic peaks at 2θ of 10.2º, 17.9º, 20.7º and 25º which demonstrates crystalline nature of the drug. CPD showed two peaks in the diffractogram at a diffraction angle of 10º and 20º indicates semi-crystalline nature of CPD. Whereas, XRD pattern of MDPF membrane exhibited more of an amorphous nature as compared to pure GLC due to shifting of its diffraction intensity, conforming GLC physical state transformed from crystalline state to amorphous state during the entrapment process in the nanofiber membrane. As shown in fig.6
Figure No 4: Overlay of Powder XRD pattern of GLC
Figure No 5: Overlay of Powder XRD pattern of CPD
Figure No 6 : Overlay Powder XRD pattern of optimized MDPF.
Differential scanning calorimetry (DSC)
DSC studies were performed to characterize the solid state of drugs and polymers. Further, compatibility between drug and excipients can be evaluated by observing the thermal behavior of compounds such as appearance or disappearance of an endothermic or exothermic peak. If all the peaks remain the same, compatibility can be expected. DSC thermogram of GLC, PMMA, PVPK90 and optimized nanofiber membrane are depicted in Figure 7. DSC thermogram of GLC showed a sharp endothermic peak at 172.13 ºC which is attributed to its melting point. The sharp melting peaks exhibited by GLC confirmed their existence as a crystalline form. Thermogram of PMMA exhibited a characteristic peak at 40ºC due to its semi-crystalline nature. The PVPK90 also exhibited characteristic peaks of all components indicating physical compatibility between excipients and drug. Whereas, optimized MDPF membrane showed flat curve without sharp endothermic or exothermic peaks of drug. This indicates that transformation of phase i.e. crystalline state to amorphous state has taken place, during the entrapment process. This might be due to shear stress provided by the stirrer and electrospinning during the fabrication process of nanofiber which may prevent there crystallization of GLC, leaving GLC in molecular dispersion form inside the MDPF membrane are shown in Figure no. 7.
Figure No. 7: DSC thermograms of GLC, PMMA, PVPK90 & Optimized formulation (MDPF)
FTIR drug – polymer compatibility studies:
FTIR spectra are shown above. The characteristic peaks of PVP K90 at 2594 cm-1 (C-H stretching), 1649.44 cm-1(C=O stretching), 1461.31 cm-1(C-H beading of CH2) and 1285.68 cm-1 (C-N stretching) are shown in Figure 1 Due to the hydrophilic nature of PVP, a broad ban was observed (O-H stretch) at about 3500 cm [18,19]
Gliclazide
Fig No: 8 FTIR spectra of pure drug Gliclazide
Table No: 2 Interpretation of FTIR spectra of GLC
|
Sr. no. |
Absorption bands at cm? 1 |
vibrations |
|
1 |
1708.34 |
C=O |
|
2 |
1432.37 |
SO2NH |
|
3 |
1346.11 |
SO2NH |
|
4 |
1162.38 |
S=O |
|
5 |
918.14 |
C-O |
|
6 |
666.36 |
CCL |
|
7 |
631.96 |
C-CL |
Fig No: 9 FTIR Spectra of Drug + PMMA+PVPK90 (COPD)
Table No: 3 Interpretation of FTIR Spectra of Drug + PMMA+PVPK90 (COPD)
|
Sr. no. |
Absorption bands at cm? 1 |
vibrations |
|
1 |
1708.42 |
Carboxylic acid |
|
2 |
1433.57 |
C-H beading |
|
3 |
1346.34 |
SO2NH stretching |
|
4 |
1162.88 |
S=O |
|
5 |
918.49 |
O-C |
|
6 |
666.38 |
C-CL |
B) MDPF
Fig No: 10. FTIR Spectra of MDPF
Table No: 4 Interpretation of FTIR Spectra of MDPF
|
Sr. no. |
Absorption bands at cm? 1 |
vibrations |
|
1 |
2970.51 |
C-H stretching |
|
2 |
1736.95 |
C=O |
|
3 |
1671.18 |
Propolis |
|
4 |
1434.60 |
C-H bending |
|
5 |
1365.77 |
SO2NH stretching |
|
6 |
1229.53 |
C-O stretching |
IN VITRO RELEASE STUDY
An in vitro study was conducted using a magnetic stirrer to investigate the release of a drug from a fiber. The experiment began by preparing a stock solution, where 100 mg of the drug-loaded fiber was added to 100 ml of phosphate buffer solution (pH 7.4), and stirred at 100 rpm for 18 hours. At hourly intervals, 1 ml of the solution was withdrawn from the stock, and an equal volume of fresh buffer solution was added to maintain the volume. Each withdrawn sample was then analyzed for absorbance at 228nm using a spectrophotometer. By analyzing the absorbance data, it was determined that approximately 95.45% of the drug had been released into the buffer solution by the end of the 18-hour period. This study provides insights into the release kinetics of the drug from the fiber in vitro, which is crucial for understanding its potential applications in drug delivery systems.
Table No .5: % of drug release on each hour
|
Sr. No. |
Time/hr |
Cumulative % Drug Release |
|
1 |
1 |
1.45 |
|
2 |
2 |
3.64 |
|
3 |
3 |
6.36 |
|
4 |
4 |
10.00 |
|
5 |
5 |
14.55 |
|
6 |
6 |
20.18 |
|
7 |
7 |
27.09 |
|
8 |
8 |
34.36 |
|
9 |
9 |
42.91 |
|
10 |
10 |
53.09 |
|
11 |
11 |
64.55 |
|
12 |
12 |
73.64 |
|
13 |
13 |
76.91 |
|
14 |
14 |
82.18 |
|
15 |
15 |
84.18 |
|
16 |
16 |
88.91 |
|
17 |
17 |
92.73 |
|
18 |
18 |
95.45 |
Figure No.11: The %of drug release at each hour
Design of Experiment:
The DoE definitive screening design aimed to screen the most influential factors affecting % drug release, thus facilitating the optimization of the electrospinning process. This type of DoE requires only a small number of runs to identify most important factors quickly and efficiently. Table no. 24 shows the parameters investigated, the levels tested for each, and the associated results. If a systematic approach was used to run experiments for all combinations of the three chosen factors at three levels for each, this would have resulted in 33 experiments. The design allowed for screening with only 17 runs, investigating the main effects of the parameters on the outputs % drug release. (82)
6.3.1 Factorial design with upper, middle & lower limit of all factor
Table No.6: factorial design with upper, middle & lower limits of all factor
|
Sr. No. |
Independent factors |
Level |
||
|
-1 |
0 |
+1 |
||
|
1 |
Polymer concentration |
12 |
14 |
16 |
|
2 |
Flow Rate |
0.03 |
0.04 |
0.05 |
|
3 |
Applied Voltage |
15 |
17 |
19 |
6.3.2 Statistical optimization technique
Design expert version 9.0.1, stat-Ease, software was used for formulation design. Formulation and evaluation of gliclazide loaded nanofiber by QbD developed by Box Behnken experimental design.
Table No.7: Box Behnken Experimental design
|
Sr. No. |
Std Run |
Factor I Polymer concentration (%) |
Factor II Flow rate(ml/min) |
Factor III Applied voltage(kV) |
Drug Release (%) |
|
1 |
14 |
14.00 |
0.04 |
17.00 |
39.52 |
|
2 |
11 |
14.00 |
0.03 |
19.00 |
31.05 |
|
3 |
7 |
12.00 |
0.04 |
19.00 |
34.36 |
|
4 |
2 |
16.00 |
0.03 |
17.00 |
50.34 |
|
5 |
12 |
14.00 |
0.05 |
19.00 |
40.21 |
|
6 |
16 |
14.00 |
0.04 |
17.00 |
33.11 |
|
7 |
4 |
16.00 |
0.05 |
17.00 |
48.02 |
|
8 |
6 |
16.00 |
0.04 |
15.00 |
44.94 |
|
9 |
17 |
14.00 |
0.04 |
17.00 |
39.52 |
|
10 |
5 |
12.00 |
0.04 |
15.00 |
25.12 |
|
11 |
3 |
12.00 |
0.05 |
17.00 |
29.27 |
|
12 |
10 |
14.00 |
0.05 |
15.00 |
36.22 |
|
13 |
9 |
14.00 |
0.03 |
15.00 |
29.3 |
|
14 |
8 |
16.00 |
0.04 |
19.00 |
56.34 |
|
15 |
1 |
12.00 |
0.03 |
17.00 |
23.55 |
|
16 |
15 |
14.00 |
0.04 |
17.00 |
39.52 |
|
17 |
13 |
14.00 |
0.04 |
17.00 |
39.52 |
The independent variables selected were the polymer concentration and flow rate when applied voltage and the dependent variables selected were the % drug release. the Box Behnken experimental trials were performed in all 17 possible combinations.
6.3.3 Data Analysis
The model parameters obtained from the analysis of variance (ANOVA) for the responses of all the formulations are shown in tables. These parameters were used to construct the model that describe the effect of the independent variables on the responses. Different batches of formulation within the experimental design were prepared to obtain the optimization results.
Final Equation in Terms of Coded Factors:
Drug Release= + 37.89+10.92* A +2.44* B + 3.30* C -2.01* AB + 0.54* AC + 0.54* BC + 2.73* A?2 – 3.26* B?2
Response 1 Drug Release
Analysis of variance (ANOVA) of formulation gliclazide loaded nanofiber (linear model)
Table No.8: Analysis of variance (ANOVA)
|
ANOVA for Response Surface Reduced Quadratic model |
||||||
|
Analysis of variance table [Partial sum of squares - Type III] |
||||||
|
Source |
Sum of Squares |
df |
Mean Square |
F Value |
p-value Prob > F |
|
|
Model |
1179.04 |
8 |
147.38 |
13.82 |
0.0006 |
significant |
|
A-Polymer Conc. |
953.53 |
1 |
953.53 |
89.40 |
< 0.0001 |
|
|
B-Flow Rate |
47.43 |
1 |
47.43 |
4.45 |
0.0680 |
|
|
C-Applied voltage |
86.99 |
1 |
86.99 |
8.16 |
0.0213 |
|
|
AB |
16.16 |
1 |
16.16 |
1.52 |
0.2533 |
|
|
AC |
1.17 |
1 |
1.17 |
0.11 |
0.7494 |
|
|
BC |
1.25 |
1 |
1.25 |
0.12 |
0.7405 |
|
|
A^2 |
31.53 |
1 |
31.53 |
2.96 |
0.1239 |
|
|
B^2 |
44.94 |
1 |
44.94 |
4.21 |
0.0742 |
|
|
Residual |
85.33 |
8 |
10.67 |
|
|
|
|
Lack of Fit |
52.46 |
4 |
13.11 |
1.60 |
0.3309 |
not significant |
|
Pure Error |
32.87 |
4 |
8.22 |
|
|
|
|
Cor Total |
1264.37 |
16 |
|
|
|
|
The Model F-value of 13.82 implies the model is significant. There is only a 0.06% chance that an F-value this large could occur due to noise. Values of "Prob > F" less than 0.0500 indicate model terms are significant. In this case A, C are significant model terms. Values greater than 0.1000 indicate the model terms are not significant. If there are many insignificant model terms (not counting those required to support hierarchy), model reduction may improve your model. The "Lack of Fit F-value" of 1.60 implies the Lack of Fit is not significant relative to the pure error. There is a 33.09% chance that a "Lack of Fit F-value" this large could occur due to noise. Non-significant lack of fit is good -- we want the model to fit.
Table No: 9
|
Std. Dev. |
3.27 |
R-Squared |
0.9325 |
|
Mean |
37.64 |
Adj R-Squared |
0.8650 |
|
C.V. % |
8.68 |
Pred R-Squared |
0.5514 |
|
PRESS |
567.19 |
Adeq Precision |
14.047 |
The "Pred R-Squared" of 0.5514 is not as close to the "Adj R-Squared" of 0.8650 as one might normally expect; i.e. the difference is more than 0.2. This may indicate a large block effector a possible problem with our model and/or data. Things to consider are model reduction, response transformation, outliers, etc. All empirical models should be tested by doing confirmation runs. "Adeq Precision" measures the signal to noise ratio. A ratio greater than 4 is desirable. our ratio of 14.047 indicates an adequate signal. This model can be used to navigate the design space.
Table No:10
|
Factor |
Coefficient Estimate |
df |
Standard Error |
95% CI Low |
95% CI High |
VIF |
|
Intercept |
37.89 |
1 |
1.30 |
34.90 |
40.88 |
|
|
A-Polymer Conc. |
10.92 |
1 |
1.15 |
8.25 |
13.58 |
1.00 |
|
B-Flow Rate |
2.44 |
1 |
1.15 |
-0.23 |
5.10 |
1.00 |
|
C-Applied voltage |
3.30 |
1 |
1.15 |
0.63 |
5.96 |
1.00 |
|
AB |
-2.01 |
1 |
1.63 |
-5.78 |
1.76 |
1.00 |
|
AC |
0.54 |
1 |
1.63 |
-3.23 |
4.31 |
1.00 |
|
BC |
0.56 |
1 |
1.63 |
-3.21 |
4.33 |
1.00 |
|
A^2 |
2.73 |
1 |
1.59 |
-0.93 |
6.40 |
1.00 |
|
B^2 |
-3.26 |
1 |
1.59 |
-6.93 |
0.40 |
1.00 |
Final equation in terms of coded factors:
Drug Release= + 37.89+10.92* A +2.44* B + 3.30* C -2.01* AB + 0.54* AC + 0.54* BC + 2.73* A?2 – 3.26* B?2
The equation in terms of coded factors can be used to make predictions about the response forgiven levels of each factor. By default, the high levels of the factors are coded as +1 and the low levels of the factors are coded as -1. The coded equation is useful for identifying the relative impact of the factors by comparing the factor coefficients.
6.3.4. Lack of fit tests table
Table No.11: lack of fit tests table
|
Lack of fit tests |
||||||
|
source |
Sum of squares |
df |
mean square |
F value |
p-value prob > F |
|
|
Linear |
143.54 |
9 |
15.95 |
1.94 |
0.2731 |
Suggested |
|
2FI |
124.96 |
6 |
20.83 |
2.53 |
0.1936 |
|
|
Quadratic |
49.60 |
3 |
16.53 |
2.01 |
0.2547 |
|
|
Cubic |
0.000 |
0 |
|
|
|
Aliased |
|
Pure Error |
32.87 |
4 |
8.22 |
|
|
"Lack of Fit Tests": Want the selected model to have insignificant lack-of-fit. |
Model Summary Statistics table
Table No.12: Model Summary Statistics table
|
Model Summary Statistics |
||||||
|
source |
Std. dev. |
R-Squared |
Adjusted R-Squared |
Predicted R-Squared |
PRESS |
|
|
Linear |
3.68 |
0.8605 |
0.8283 |
0.7344 |
335.87 |
Suggested |
|
2FI |
3.97 |
0.8752 |
0.8003 |
0.4685 |
672.02 |
|
|
Quadratic |
3.43 |
0.9348 |
0.8509 |
0.3317 |
844.92 |
|
|
Cubic |
2.87 |
0.9740 |
0.8960 |
|
+ |
Aliased+ Case(s) with leverage of 1.0000: PRESS statistic not defined "Model Summary Statistics": Focus on the model maximizing the "Adjusted R-Squared" and the "Predicted R-Squared". |
Sequential Model Sum of Squares Table
Table No.13: Sequential Model Sum of Squares Table
|
Sequential Model Sum of Squares [Type I] |
||||||
|
source |
Sum of squares |
df |
Mean square |
F value |
p-value Prob > F |
|
|
Mean vs Total |
24087.34 |
1 |
24087.34 |
|
|
|
|
Linear vs Mean |
1087.96 |
3 |
362.65 |
26.72 |
< 0.0001 |
Suggested |
|
2FI vs Linear |
18.58 |
3 |
6.19 |
0.39 |
0.7612 |
|
|
Quadratic vs 2FI |
75.37 |
3 |
25.12 |
2.13 |
0.1844 |
|
|
Cubic vs Quadratic |
49.60 |
3 |
16.53 |
2.01 |
0.2547 |
Aliased |
|
Residual |
32.87 |
4 |
8.22 |
|
|
|
|
Total |
25351.71 |
17 |
1491.28 |
|
|
"Sequential Model Sum of Squares [Type I]": Select the highest order polynomial where the additional terms are significant and the model is not aliased. |
Summary table
Table No.14: summary table
|
Summary (detailed tables shown below) |
|||||
|
source |
Sequential p-value |
Lack of fit p-value |
Adjusted R-Squared |
Predicted R-Squared |
|
|
Linear |
< 0.0001 |
0.2731 |
0.8283 |
0.7344 |
Suggested |
|
2FI |
0.7612 |
0.1936 |
0.8003 |
0.4685 |
|
|
Quadratic |
0.1844 |
0.2547 |
0.8509 |
0.3317 |
|
|
Cubic |
0.2547 |
|
0.8960 |
|
Aliased |
figure No.12: normal plot of residual graph Normal % probability vs externally studentized residuals
Figure No.13: counter plot for indivuals response with respect to predicted vs actual
Figure No.14: counter plot showing combined effect of polymer concentration and flow rate when applied voltage kept at lower level i.e. 17.92
Figure No.15: 2D- 3D Response surface plot showing combined effect counter plot showing combined effect of polymer concentration and flow rate when applied voltage kept at lower level i.e. 17.92
Figure No.16: counter plot showing combined effect of polymer concentration and applied voltage when flow rate kept at lower level i.e. 0.04
Figure No.17: 2D- 3D Response surface plot showing combined effect counter plot showing combined effect of polymer concentration and applied voltage when flow rate kept at lower level i.e. 0.04
Figure No.18: counter plot showing combined effect of flow rate and applied voltage when polymer concentration kept at lower level i.e. 15.73
Figure No.19: 2D- 3D Response surface plot showing combined effect counter plot showing combined effect of flow rate and applied voltage when polymer concentration kept at lower level i.e. 15.73
Figure No.20: desirability plot for optimization for formulation and evaluation of gliclazide loaded nanofiber
CONCLUSION:
The nanofibre formulation carried by the electrospinning method as per QbD approach in the proper manner and effectively nanofibers made by standard procedures set and work carried out. The effect of drug: polymer on the physical characteristics of the formulated nanofibre was examined for various drug: polymer ratios of nanofibers at stirring speed of 400-600rpm for 1hrs by electrospinning method. The mean particle size of nanofibers can be influenced by drug: polymer ratio. It was observed that as drug: polymer ratio increases, the particle size decreased. The effect of stirring rate on the physical characteristics of the formulated nanofibers was examined for 7: 3 polymer ratio nanofibers. The stirring rate was varied in the range of 400-600rpm. Polymer concentration has a crucial role in making characterized nanofibers given concentration of polymer gives uniform and structured nanofibers and with optimum release of drug with the help of accurate set ratios of polymer concentration, flow rate, distance between needle and collector, voltage these parameter setted as per the QbD approach. PMMA proportion in NF resulted in an increase in the viscosity of the solution higher viscosities resulted into formation of dense network of the polymer preventing the drug from leaving the matrix. In FTIR analysis obtained results shows that no interaction between drug, polymer and formulation occurred because no change in the characteristics peak was seen. Hence drug and selected polymer were compatible with each other. In SEM analysis result shows that fibre mat found to be smooth continuous fibre structured 627.9±149.78 nm respectively. As the viscosity of solution increased, entanglement in polymer chain also increased. Fibers were prepared without the occurrence of bead defects. It was remarkable to note. In DSC analysis result the drug and polymer melting point determined as per standard values with the help of the endothermic and exothermic reactions with respective drug and polymer used for the nanofibre formulation. In in-vitro drug release studies for all gliclazide nanofibers, formulations along with pure gliclazide were performed and are reported in result section figure No. All gliclazide loaded nanofibers formulations have shown significant enhancement in dissolution rate compared to pure gliclazide in PBS dissolution media at pH 7.4. Using standard least squares regression analysis model, a predictive tool was used to predict % drug release. To determine the reliability of the predictive model, a summary of the fit is shown in Figure no. 24. The regression model for the reduction of % drug release data had an R2 of 0.93, which means that 93% of the predicted % drug release are within the confidence intervals of the actual % drug release recorded. Similarly, the predicted beading regression analysis, R2 = 0.93, also had a very positive correlation with the actual % drug release recorded, showing that 93% of the model predictions are within the confidence intervals of the actual % drug release data recorded. Both confidence curves cross the horizontal lines, which indicate that the predictions are statistically significant to the actual measurements. The main effects of polymer concentration, applied voltage, flow rate, have so far been discussed in the electrospinning of polymer concentration. The DoE completed for manufacturing optimization of polymer concentration aimed at screening for the most influential factors. Multifactorial interactions are useful to gain a deeper understanding of the electrospinning process. Thirty-Four experiments of drug-loaded polymer conc. were completed. The effect of each parameter and multifactorial interactions were investigated on % drug release. The purpose of this study was to fabricate drug-loaded fibers and establish a proof of concept for the electrospun method of making electrostatic fiber as a functional specialized carrier system for oral delivery of gliclazide in type 2 diabetes mellitus (T2DM). The drug delivery challenges associated with oral gliclazide delivery are poor solubility, low dissolution rate, variable gastrointestinal absorption and erratic bioavailability. In this research, gliclazide loaded PMMA/PVPK90 electrostatic fibers were successfully fabricated to improve the drug delivery challenges with enhanced drug dissolution and a modified drug release profile employing the emulsion electrospinning method. The formulation composed of PMMA: PVPK90: Drug in a 7:3:15% w/v ratio produced optimized and desired gliclazide nanofibers. The optimized formulation of gliclazide loaded nanofibers was incorporated into an empty gelatin capsule for oral administration. To establish electrostatic fibers as a functional specialized carrier system for oral delivery, the developed gliclazide nanofibers were extensively investigated for morphological and physicochemical characterizations such as solubility studies, in vitro drug release studies, drug release kinetic studies, scanning electron microscopy studies (SEM), differential scanning calorimetric (DSC) studies and Fourier transform infrared (FTIR) spectroscopy studies. The SEM image of optimized gliclazide nanofibers formulation shows the cylindrical shape of fiber indicates gliclazide was incorporated homogeneously in the polymer. The solubility and dissolution rate of gliclazide nanofibers were significantly improved compared to pure gliclazide. This study also highlights that optimized gliclazide nanofibers formulation, developed with PMMA/PVPK90, successfully achieved a modified drug release to meet the typical physiological needs of T2DM, such as a faster drug release at the time of meals followed by prolonged drug release profile over an extended period to maintain constant plasma glucose level, highly desirable in T2DM management. Fabricated gliclazide fibers in oral dosage form have tremendous potential as a drug carrier and alternative technology for the improvement of solubility, dissolution rate, reduction in the dosing frequency and better blood glucose control, and could be explored in T2DM management. Gliclazide nanofibers formulation was formulated effectively by QbD approach with the help of box benken diagram gives 3D graph of our formulation the optimization of prepared NF gives increased release of the drug through the nanofibers. As concept involved is novel and methodology used for preparation is simple as that of other nano formulations regarding diabetes mellitus and formulated nanofibers can be developed for tablet, capsule formulation which can be used in diabetes patients. In vitro drug diffusion studies indicated that the developed M-4 was found to be the best formulation containing 0.1gm of gliclazide drug, polymer ratio 7:3 with added benefits of sustained drug release which may ultimately result into improved patient compliance.
REFERENCES
Dr. Omprakash Bhusnure, Manisha Mashalkar, Dr. Mani Ganesh, Dr. Vijayendra Swammy, Dr. Hyun Tae Jang, Formulation, Characterization and Evaluation of Gliclazideloaded Nanofiber for Diabetes Management by QbD Approach, Int. J. of Pharm. Sci., 2025, Vol 3, Issue 6, 5554-5574. https://doi.org/10.5281/zenodo.15763602
10.5281/zenodo.15763602