OPTIMIZATION OF VARIOUS PROCESS PARAMETERS FOR FORMULATION OF MODEL ANTI-HYPERLIPIDEMIC DRUG BY USING DRY GRANULATION METHOD
HTML Full TextOPTIMIZATION OF VARIOUS PROCESS PARAMETERS FOR FORMULATION OF MODEL ANTI-HYPERLIPIDEMIC DRUG BY USING DRY GRANULATION METHOD
Himankar Baishya*, Athappan Chidambaram and Zhao Haitho
Senior Director, R & D, Beijing Sciecure Pharmaceuticals Co., Ltd., Beijing, China
ABSTRACT: The Tablet manufacturing process is a complex process, influenced by several process variables The aim of this study was to optimize blending; roller compaction and tablets compression processes using design space approach for a model Anti- Hyperlipidemic drug Fluvastatin. During each processes there are several factors which may affect product quality. So the main objective of present work was to identify various parameters and optimize the parameter for formulation of better product which includes Blending time, Roller force, Compression force and machine speed which were recognized as critical process parameters and were evaluated. A scale up batch is taken to evaluate and optimize the parameters. Critical quality attributes like Blend uniformity, granules parameters, flow behavior, tablet appearance, impact on tablet physical parameters and in-vitro drug dissolution release profile is evaluated to optimize the parameters. The data & test results of blend, granules and tablets at various in-process phases were complied with the specified limits and finished product sample analysis results found to be complying within specifications. This study and results obtained assures that the manufacturing process is reproducible, robust and will yield consistent product, which meets specification.
Keywords: |
Tablet, Anti- Hyperlipidemic, In-vitro, Granulation
INTRODUCTION: Quality by Design (QbD):
Recently proposed quality-by-design (QbD) regulatory initiative of pharmaceutical product and process development has encouraged researchers in pharmaceutical industry to reach the “desired state” of drug manufacturing in 21st century. Main goal of this approach is to gain a comprehensive understanding of their manufacturing processes, with an accurate estimation of their robustness and reliability.
The emphasis has changed from the need to demonstrate that the product will consistently meet relatively tight specifications to a new situation of being able to demonstrate that the product is controlled within a broader “design space” (DS). The design space (DS) concept is introduced as “the multidimensional combination and interaction of input variables (e.g., materials attributes) and process parameters that have been demonstrated to provide assurance of quality.”
Using this approach, it is essential to define relationship between critical formulation/process parameters and critical quality attributes (such as granule characteristics and tablet properties. A simplified quality assurance diagram under the QbD for drug product development is schematically represented in Fig. 1.1, 2
TABLE 1: A SIMPLIFIED QUALITY ASSURANCE DIAGRAM UNDER THE QBD FOR GENERIC DRUGS 2
Process Optimisation:
The development and commercial release of a globally marketed pharmaceutical drug product necessarily begins in the realm of the very small. Drug discovery may focus on the molecular level, and early formulation may deal with only gram quantities of material. It is at the early formulation stage, however, that a tentative sequence of physico chemical operations is initially
Proposed and developed to transform the raw materials into a drug product with the desired quality attributes (e.g., potency, dissolution, etc.) At this early stage, these experimental operations are carried out in bench top or small pilot-scale equipment, and the process knowledge in the form of raw data obtained from these experiments is specific to that scale. Process optimization is the practice by which process knowledge is developed and formulated in such a way that it can be applied effectively to guide equipment selection process parameters, process conditions, and process control strategies, irrespective of scale.3, 4
An HPMC based extended release tablet formulation of a model anti-Hyperlipidemic drug is developed by dry granulation process. The manufacturing stages involve sifting, blending, blend lubrication, roller compaction, compression and coating.
The aim of our study was to define the design space of Blending operation, dry granulation and tablet compression process. In the first part, the assessment of process and formulation factors (critical material and process parameters) and their influence on critical quality attributes of intermediate and finished product was performed. Dry granulation parameters and compression force were varied, in order to develop new design space, evaluating their influence on tablets characteristics.
MATERIALS AND METHODS:
Materials:
Materials used in the presented study for the granulation and tableting experiments were: Fluvastatin sodium (TEVA API India limited.), Glyceryl behenate (Compritol 888 ATO, Gattefosse), Pregelatinized Starch (Starch 1500 - Colorcon), Hypromellose (Methocel K100LV CR - Colorcon), Hypromellose (Methocel K15MCR - Colorcon), Potassium Hydrogen Carbonate (Merck KgaA Germany), Magnesium Stearate (Peter Graven) and Opadry Yellow 81W42236 (Colorcon)
Manufacturing procedure:
Matrix tablets were prepared by dry granulation method with the formula optimized composition as given in Table 1.
TABLE 1: FINAL FORMULA COMPOSITION TO BE PROCESS OPTIMSED FOR
Sl.no | Name of the Raw Material | mg/tablet |
Core Tablets | ||
1 | Fluvastatin sodium | 84.28 |
2 | Glyceryl Behenate | 50.00 |
3 | Pregelatinized Starch | 81.72 |
4 | Hypromellose (Grade A) | 34.00 |
5 | Hypromellose(Grade B) | 32.00 |
6 | Potassium Hydrogen Carbonate | 13.00 |
7 | Magnesium Stearate | 5.00 |
Core Tablet weight | 300.0 | |
Coating agent | ||
8 | Opadry Yellow | 3.00 |
9 | Purified Water | NA |
Coated Tablet weight | 303.0 |
The manufacturing procedure for tablet production is as follows: Fluvastatin Sodium and other excipients except Magnesium Stearate were initially passed through 20# sieve. The sifted material is blended for suitable time interval in a lab scale bin blender. The blended material is lubricated with Magnesium Stearate sifted through #40 sieve for 5 minutes. The lubricated blend is compacted in Alexanderwerk WP200 roller compactor at suitable parameters to arrive at desired granular material. The obtained granules were lubricated with extra granular Magnesium Stearate for 5 minutes and resulting granules were evaluated for the flow properties. Tablets were compressed using 10.0 mm round shaped punches on KORSCH XM-12 compression machine. As per the process optimization plan different critical process parameters were evaluated and studied for their effect on critical quality attributes or quality target product profile (QTPP) of products.
The details of equipments used for various manufacturing process and their capacities areas listed in Table 2.
TABLE 2: LIST OF EQUIPMENT UTILIZED FOR BATCH MANUFACTURING
Manufacturing Stage | Equipment used | Capacity | Manufacturer, Model No |
Dispensing | Dispensing Booth | Not Applicable | March-Aire , 3300DFB |
Sifting | Vibrosifter | Not Applicable | Jiangsu Gui Bao, ZS 350 |
Blending | Bin blender | 10L,30L,50L and 100L | Zhejiang Canaan, HSD 100 |
Blend lubrication | Bin blender | 10L,30L,50L and 100L | Zhejiang Canaan, HSD 100 |
Roller compaction | Alexanderwerk WP200 | 200 Kg/ hour | WP200 |
Granules lubrication | Bin blender | 10L,30L,50L and 100L | Zhejiang Canaan, HSD 100 |
Compression | KORSCH XM 12 Compression machine | 6 station
Single layer and bi-layer Max speed: 60rpm |
KORSCH XM 12 |
Coating | Glatt GMPC II | Glatt GMPC II | 9L, 56L |
Based on scientific understanding and prior knowledge, a risk assessment of the potential impact of the unit operations on the drug product CQAs was completed. Table 3 shows the result of the risk assessment and identifies the unit operations which require further investigation to determine the appropriate control strategy.
TABLE 3: RISK MATRIX FOR DRUG PRODUCT CQAS FOR EACH UNIT OPERATION
Unit operation | |||||
DP CQAs | Blending | Blend Lubrication | Roller compaction | Granules lubrication | Compression |
Appearance | Low | Low | Low | Low | High |
Identity | Low | Low | Low | Low | Low |
Assay | Low | Low | Low | Low | High |
Content uniformity | High | High | High | High | High |
Dissolution | Low | Low | High | Low | High |
Process Optimization – Blending and Blend Lubrication Unit Operation:
The manufacturing process uses a blending step followed by roller compaction to obtain granules for compression. The blend includes approximately 26% active and 74% excipients, which is mostly Glyceryl behenate and Pregelatinized Starch. Despite the presence of roller compaction and granules blending step (lubrication) later in the process train, this processing step was deemed critical because development studies indicated that material insufficiently blended or lubricated at this stage ultimately leads to unacceptable content uniformity of the finished drug product and roller sticking tendency during compaction respectively. Blending process was done for 12 minutes at 12 rpm with intermittent sampling was done at 4 minutes, 8 minutes and 12 minutes. The 12 minutes blended material is lubricated for 5 minutes at 12 rpm with intermittent sampling at 3 minutes and 5 minutes. Details is as listed in Table 4.
TABLE 4: PROCESS PARAMETERS FOR BLENDING AND BLEND LUBRICATION BATCH SIZE – 40, 000 TABLETS, 12.0 KG
Blending | Blend Lubrication | ||||
Batch No | Trial 1 | Trial 2 | Trial 3 | Trial 1 | Trial 2 |
Machine RPM | 12 RPM | 12 RPM | 12 RPM | 12 RPM | 12 RPM |
Blending time (minutes) | 4 minutes | 8 minutes | 12 minutes | 3 minutes | 5 minutes |
Total Revolution | 48 revolutions | 96 revolutions | 144 revolutions | 36 revolutions | 60 revolutions |
The sampled materials are analyzed for individual blend content uniformity as per the approved method and evaluated for blend content uniformity at various blending time intervals.
Process Optimization – Roller compaction unit operation: 5, 6
The purpose of the roller compaction and milling stages is to produce granulated product that is suitable for subsequent blending and compression. The initial blend is transferred to the roller compactor where a screw-feeder drives it between two rollers, which compact the material. The compacted ribbon is then broken up and passes through a rotating impellor screen mill. Critical process parameter for roller compaction process is Roller force, roller gap, roller speed and mill screen size. The parameters under evaluation are Roller force, roller gap and roller speed. A design experiment of 2 Level Factorial design with 1 center point is applied to evaluate the roller compaction parameters on critical quality attributes of drug product. The compacted granules are lubricated and compressed into tablets at pre-determined parameters. The factors and range for roller compaction parameter studied is as in Table 5.
TABLE 5: FACTOR STUDIED (CRITICAL PROCESS PARAMETERS)
Factor | Name | Units | Minimum | Maximum |
Factor 1 | Roller Force | Bar | 30 | 50 |
Factor 2 | Roller Speed | mm | 3 | 9 |
Factor 3 | Roller Gap | rpm | 2 | 4 |
TABLE 6: DOE RUN DETAILS, BATCH SIZE – 40, 000 TABLETS, 12.0 KG
Trial 1 Lubricated Blend | ||||||||||
Run | Units | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 |
A: Force | KN/cm | 30 | 50 | 30 | 50 | 40 | 50 | 30 | 50 | 30 |
B: Gap | mm | 4 | 4 | 2 | 4 | 3 | 2 | 2 | 2 | 4 |
C: Speed | rpm | 3 | 3 | 3 | 9 | 6 | 9 | 9 | 3 | 9 |
For tracking and understanding the granules are coded as Trial 1-A to Trail 1-I. The impact of these parameters on Critical Quality Attributes of Drug Products and Intermediates like Bulk density, Tapped density, PSD #60 meshes Cum. % retained and tablet dissolution profile is studied.
Process Optimization – Granulation Lubrication Unit Operation:
Following the roller compaction and milling, the milled granulation is blended with extragranular excipients in a third blending operation. The granules are mixed with 1.0% magnesium stearate (as lubricant). Based on the development data, the blending parameter targets listed in Table 7 are acceptable for the proposed commercial scale lubrication blending process. Because studies have shown that wide variations in both blending time and blender fill volume have negligible impact on any CQA, this unit operation is considered robust and has no critical process parameters.
TABLE 7: PROCESS PARAMETERS FOR GRANULES LUBRICATION
Batch Size – 40, 000 Tablets, 12.0 kg
Granules Lubrication | |
Batch No | Trial 1 |
Machine RPM | 12 RPM |
Blending time (minutes) | 5 minutes |
Total Revolution | 60 revolutions |
The sampled materials are analyzed for individual blend content uniformity as per the approved method and evaluated for blend content uniformity at various blending time intervals. No further optimisation is being done for this unit operation.
Compression process parameters: 7, 8
During compression of the tablet, Compression Force (Pre-Compression and Main Compression) and machine speed should be optimized. Compression parameters for compression force and speed stud study are shown in Table 8 and 9 respectively. Tablets of these batches were evaluated for Thickness, Weight variation, Friability and dissolution study.
TABLE 8: COMPRESSION FORCE STUDY
Batch Size – 40, 000 Tablets, 12.0 kg
Parameter | Optimization batch | |||
High compression force | Target compression force | Low compression force | Without pre-compression force | |
Pre-compression force (Kn) | 8.5 | 3.2 | 1.4 | 0.2 |
Main compression force (Kn) | 36.1 | 23.1 | 17.3 | 13 |
Dosing (mm) | 5.1 | 4.9 | 5.1 | 5.1 |
Machine RPM | 15 | 15 | 12 | 12 |
TABLE 9: COMPRESSION MACHINE SPEED STUDY
Parameter | Optimization batch | ||
High speed – 40 RPM | Target speed - 20 RPM | Low speed - 10 RPM | |
Main compression force (Kn) | 23.1 | 23.1 | 23.1 |
Dosing (mm) | 4.9 | 4.9 | 4.9 |
Machine RPM | 40 | 20 | 10 |
RESULTS AND DISCUSSION:
Process Optimization – Blending and Blend Lubrication Unit Operation:
For batch No coded as Trail 1, blend uniformity data at blending stage and blend lubrication stage is tabulated in Table 9 and graphical representation of % RSD with mixing time is shown in Figure 2 and 3. From the results we can say that % RSD is less than 4.0% at all time intervals. At blending stage with increase in blending time from 4 minutes to 12 minutes the % RSD is minimum and content uniformity is improved. Also with blend lubrication the % RSD reduced to less than 2.0% at 5 minutes blend lubrication time. So finally 12 minutes of blending time and five minutes of blend lubrication time was finalized.
TABLE 10: BLEND UNIFORMITY DATA AT BLENDING AND BLEND LUBRICATION STAGE
Fluvastatin ER Tablets 80 mg – Trail 1 | |||||
Sample | Blending stage | Blend Lubrication | |||
4 minutes | 8 minutes | 12 minutes | 3 minutes | 5 minutes | |
% drug content (Fluvastatin) | |||||
A | 95.8 | 94.2 | 101.1 | 96.0 | 97.1 |
B | 99.9 | 101.2 | 99.3 | 103.5 | 99.8 |
C | 105.5 | 99.7 | 100.7 | 103.0 | 98.8 |
D | 96.9 | 98.3 | 101.5 | 99.0 | 100.8 |
E | 96.6 | 98.8 | 100.0 | 97.2 | 101.3 |
F | 96.8 | 101.8 | 100.2 | 102.2 | 98.7 |
G | 101.7 | 100.3 | 100.9 | 95.6 | 100.3 |
H | 98.0 | 100.7 | 103.0 | 98.7 | 101.0 |
I | 97.6 | 101.8 | 104.0 | 101.3 | 102.2 |
J | 99.4 | 98.6 | 100.4 | 99.2 | 98.5 |
Minimum | 95.8 | 94.2 | 99.3 | 95.6 | 97.1 |
Maximum | 105.5 | 101.8 | 104.0 | 103.5 | 102.2 |
Mean | 98.8 | 99.5 | 101.1 | 99.57 | 99.9 |
%RSD | 2.99 | 2.28 | 1.39 | 2.85 | 1.57 |
FIG.2: COMPARISON OF BLEND UNIFORMITY DATA AT DIFFERENT BLENDING TIME INTERVALS FOR FLUVASTATIN ER TABLETS 80 MG
FIG.3: COMPARISON OF BLEND UNIFORMITY DATA AT DIFFERENT BLEND LUBRICATION TIME INTERVALS FOR FLUVASTATIN ER TABLETS 80 MG
Process Optimization – Roller compaction unit operation:
The trial batch In-process data for granules parameter and Dissolution profile for tablets at various time points is collated in tabular form. The analysed results, statistical data, Tablet parameters and dissolution profile are tabulated in Table 10 – 13. The statistical summary for the Design of experiments factorial model is tabulated in Table10. The contour plot, Pareto chart and Overlay plot for effect of model on evaluated parameters is as in Fig. 4 and 5.
TABLE 11: DOE RUN DETAILS AND OBSERVATIONS
STD No | Run | A: Force | B: Gap | C: Speed | Bulk Density | PSD #60 mesh Cum. % retained | Dissolution water 2 hr | Dissolution water 4 hr | Dissolution water 6 hr | Dissolution water 8 hr |
Unit | BAR | mm | RPM | g/mL | % | % | % | % | % | |
3 | 1 | 30 | 4 | 3 | 0.491 | 39.68 | 18 | 45 | 71 | 95 |
4 | 2 | 50 | 4 | 3 | 0.554 | 68.74 | 20 | 46 | 73 | 96 |
1 | 3 | 30 | 2 | 3 | 0.509 | 53.76 | 18 | 43 | 69 | 92 |
8 | 4 | 50 | 4 | 9 | 0.551 | 64.94 | 19 | 45 | 72 | 93 |
9 | 5 | 40 | 3 | 6 | 0.544 | 62.16 | 18 | 45 | 72 | 92 |
6 | 6 | 50 | 2 | 9 | 0.583 | 66.63 | 21 | 46 | 74 | 94 |
5 | 7 | 30 | 2 | 9 | 0.5 | 54.94 | 17 | 37 | 64 | 91 |
2 | 8 | 50 | 2 | 3 | 0.552 | 72.2 | 21 | 46 | 74 | 97 |
7 | 9 | 30 | 4 | 9 | 0.488 | 44.59 | 16 | 39 | 67 | 95 |
TABLE 12: DOE SUMMARY: STATISTICAL ANALYSIS
ANOVA Analysis | Bulk density | PSD #60 mesh Retained | Dissolution 2 hour | Dissolution 4 hour | Dissolution 6 hour | Dissolution 8 hour | ||||||
p- values | Signal. Response effect | p- values | Signal. Response effect | p- values | Signal. Response effect | p-
values |
Signal. Response effect | p- values | Signal. Response effect | p- values | Signal. Response effect | |
Model | 0.006 | Yes | 0.006 | Yes | 0.008 | Yes | 0.081 | NA | 0.059 | NA | 0.339 | NA |
Roller Force | 0.001 | Yes | 0.001 | Yes | 0.002 | Yes | 0.035 | yes | 0.019 | yes | 0.2492 | No |
Roller Gap | 0.13 | No | 0.061 | No | 0.082 | No | 0.648 | No | 0.745 | No | 0.3904 | No |
Roller Speed | 0.639 | No | 0.801 | No | 0.082 | No | 0.099 | No | 0.157 | No | 0.2492 | No |
TABLE 13: TABLET PHYSICAL PARAMETERS FOR TABLETS COMPRESSED USING GRANULES COMPACTED AT DIFFERENT PARAMETERS
Parameter | |||||||||
Trial 1- A | Trial 1-B | Trial 1-C | Trial 1-D | Trial 1-E | Trial 1-F | Trial 1-G | Trial 1-H | Trial 1-I | |
Individual weight(mg) | 299 - 306 | 306 - 313 | 299 - 308 | 300 - 305 | 295 - 306 | 291 - 306 | 298 - 305 | 298 - 308 | 299 – 304 |
Thickness(mm) | 4.11 - 4.20 | 4.14 - 4.25 | 4.10 - 4.20 | 4.08 - 4.12 | 4.14 - 4.22 | 4.14 - 4.24 | 4.15 - 4.24 | 4.18 - 4.26 | 4.18 -4.24 |
Hardness(N) | 52 - 61 | 52 - 68 | 60 - 65 | 52 - 65 | 55 - 64 | 39 - 50 | 52 - 64 | 50 - 64 | 51 – 62 |
Friability (1%) | Nil | Nil | Nil | Nil | Nil | nil | nil | Nil | Nil |
Flow Properties | Good | Good | Good | Good | Good | Good | Good | Good | Good |
Table 11 shows the tablet physical testing results of tablets prepared using different granules using roller compaction granulation parameter. Data show goods similarity between different roller compaction parameter. The results also show that the speed at which the roller compactor equipment was operated at did not influence tablet crushing strength values.
TABLE 14: TABLET DISSOLUTION PROFILE FOR TABLETS COMPRESSED USING GRANULES COMPACTED AT DIFFERENT PARAMETERS
Dissolution Profile in Water at 50 rpm | Tablet dissolution Profile for tablets compressed using granules compacted at different parameters | ||||||||
Trial 1- A | Trial 1-B | Trial 1-C | Trial 1-D | Trial 1-E | Trial 1-F | Trial 1-G | Trial 1-H | Trial 1-I | |
Time point in Hours | Condition – Water, 1000 ml, USPI-I(Basket ), Sampling at 2 Hours, 4 hours, 6 hours and 8 hours | ||||||||
2 Hours | 18 | 20 | 18 | 19 | 18 | 21 | 17 | 21 | 16 |
4 Hours | 45 | 46 | 43 | 45 | 45 | 46 | 37 | 46 | 39 |
6 Hours | 71 | 73 | 69 | 72 | 72 | 74 | 64 | 74 | 67 |
8 Hours | 95 | 96 | 92 | 93 | 92 | 94 | 91 | 97 | 95 |
FIG.4: THE CONTOUR PLOT AND PARETO CHART FOR EFFECT OF MODEL ON EVALUATED PARAMETERS
FIG.5: THE MULTIPLE RESPONSES OVERLAY PLOT AT DIFFERENT ROLLER SPED (3 RPM, 6 RPM AND 9 RPM)
FIG.6: IN-VITRO DRUG RELEASE PATTERN OF FORMULATIONS TRIAL 1-A TO TRIAL 1 I IN COMPARISON TO MARKETED PRODUCT IN WATER
For all the 9 different granules the granules bulk density and particle size distribution was evaluated and found to be satisfactory. There was no flow problem during compression nor tablet sticking tendency during compression.
Roller pressure is the significant factor affecting all product attributes tested, but the operating range tested is within the design space (30 – 50 Bar). Roller gap may effect on the product attributes but not significant. Therefore the design space is what the operating range tested (2 - 4 mm). Roller speed was determined not to be critical process parameters. Therefore the design space is what the operating range tested (3 - 9 rpm). However the design space (overlay plot) indicates that at roller RPM of 9, the process gives a satisfactory properties for the granules. At 3 and 6 rpm the Dissolution at 4 hours is on the higher side out of the specification limit. Further studies to be continued to optimize the process or to identify the acceptable dissolution release profile.
- Process Optimization – Compression unit operation:
Post compression parameters such as thickness, hardness, friability, weight variation are given in following Table 14. As shown in Fig.7, there was no effect on dissolution profile of tablet produced at different compression force. There was no capping or sticking defects for the compressed tablets at different compression force. Therefore the evaluated main-compression range of 36 – 13 Kn is suitable to achieve tablets of desired quality attributes. Also with minimal pre-compression force of 0.2 Kn the binding of tablets were still reasonably good, as depicted in tablet parameters.
TABLE 14: TABLET PHYSICAL PARAMETERS FOR TABLETS COMPRESSED AT DIFFERENT COMPRESSION PARAMETER
Parameter | Compression force study | |||
High compression force | Target compression force | Low compression force | Without pre-compression force | |
Individual weight(mg) | 296 - 306 | 297 - 300 | 295 - 302 | 305 - 308 |
Thickness(mm) | 4.06 - 4.15 | 4.07 - 4.13 | 4.10 - 4.14 | 4.27 - 4.36 |
Hardness(N) | 55 - 65 | 54 - 64 | 54 - 60 | 43 - 56 |
Friability (1%) | Nil | nil | nil | Nil |
Flow Properties | Good | Good | Good | Good |
FIG.7: IN-VITRO DRUG RELEASE PATTERN OF FORMULATIONS COMPRESSED AT VARYING COMPRESSION FORCE IN COMPARISON TO MARKETED PRODUCT IN WATER
CONCLUSION: Tablet manufacturing by Dry granulation using roller compaction process is a widely used manufacturing process for poorly soluble drug having low bulk density. In manufacturing process, there are many factors which may affect final product. In this study all these critical process parameters were identified and optimized. Blending time and lubrication time in blender was also optimized. During roller compaction process the critical parameters were optimized using 3 factorial design with zero blocks. Roller compaction force is identified as the critical parameter affecting granules properties. During compression process, there was Tablet hardness which may affect release profile of drug. These parameters were also optimized. Finally its of the opinion that all the process parameters for formulation of Fluvastatin ER Tablets 80 mg by using Dry Granulation process were optimized to make the process a robust and reproducible in scale up manufacturing.
ACKNOWLEDGEMENT: We are extremely gratified to Formulation development Department and fellow colleagues, for helping us in the technical aspect of the project and also for useful scientific discussions, which produced methodical results and also for sharing their passion for drug product development and thus helping us in better understanding of critical process and quality attributes for drug development.
REFERENCES:
- EMA, 2014. Human Regulatory, Quality by Design, Guidance Documents. Accessed on 2016.06.13
- Edina Pallagi, Rita Ambrus, Piroska Szabó-Révész, Ildikó Csóka. Adaptation of the quality by design concept in early pharmaceutical development of an intranasal Nanosized formulation. International Journal of Pharmaceutics. 2015; 491:384 – 392.
- Venkateswara Reddy, K. Navaneetha, K. Venkata Ramana Reddy. International Journal of Pharmacy and Pharmaceutical Sciences.2014; 6(4):312 – 317.
- Gurpreet Kaur, D.B. Sridhar, Manoj Gera. Optimization of Roll Compaction/Dry Granulation Process for Poorly Flowable Antiviral Formulation. Am. J. PharmTech Res. 2012; 2(4): 544 – 557.
- Milad Khorasani et al., Process optimization of dry granulation based tableting line: Extracting physical material characteristics from granules, ribbons and tablets using near-IR (NIR) spectroscopic measurement
- Richard Hwang, Robert M. Noack. Application of design of experiments to pharmaceutical formulation development; 2(1): 58 – 65.
- Stephanie Sutton. Optimizing Tableting Processes with Quality by Design. Pharmaceutical Technology. 2012; 36(5).
- Ales Belic, Igor Skrjanc, Damjana Zupancic Bozic, Franc Vrecer. Tableting process optimisation with the application of fuzzy models. International Journal of Pharmaceutics. 2010; 389(1-2): 86-93
How to cite this article:
Baishya H, Chidambaram A and Haitho Z: Optimization of various process parameters for formulation of model anti-hyperlipidemic drug by using dry granulation method. Int J Pharm Sci Res 2016; 7(10): 3959-60.doi: 10.13040/IJPSR.0975-8232.7(10).3959-70.
All © 2013 are reserved by International Journal of Pharmaceutical Sciences and Research. This Journal licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License.
Article Information
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3959-70
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English
IJPSR
Himankar Baishya*, Athappan Chidambaram and Zhao Haitho
Senior Director, R & D, Beijing Sciecure Pharmaceuticals Co., Ltd., Beijing, China
himankar@sciecure.com
19 May, 2016
13 June, 2016
09 August, 2016
10.13040/IJPSR.0975-8232.7(10).3959-70
01 October 2016