OPTIMIZATION OF ALBENDAZOLE 400 MG TABLET COMPRESSION PROCESS USING DESIGN OF EXPERIMENT (DOE) APPROACH
Objective: The present study aims to model and optimize the compression process of the Albendazole 400 mg tablets of a pharmaceutical industry production line to increase the production speed (tablets/h) while maintaining quality requirements.
Methods: The study was conducted using the Design of Experiments (DoE) methodology to identify and correlate the critical parameters during the process that affect the maintenance of the compression speed. In order to support the experiments, was tested disintegration time, average hardness, hardness variation, average weight, and friability.
Results: Was obtained that quality attributes of disintegration and friability did not generate a significant model but it has been established correlations between Fill-O-Matic speed and main compression force in the responses of weight variation, hardness, and mean hardness. It was found that the main compression force between 6 to 9 kN, the pre-compression force of 1,965 to 5,615 kN, and the speed of 55 RPM for Fill-O-Matic speed are responsible for ensuring that all quality attributes analyzed remain within the expected specification.
Conclusion: It was possible to apply the Design of Experiment (DoE) methodology in the compression process of the drug Albendazole 400 mg and to evaluate the impact of the parameters of this step on the formation of the tablet to significantly increasing the productivity of this product. The Fill-O-Matic speed parameter was the main control factor discovered in this study to maintain quality attributes.
2. Gamlen M, Tableting G, Domingue J. Tabletting making better tablets: a QbD approach. Tablets and Capsules; 2014. p. 1-6.
3. Tye CK, Sun C, Amidon GE. Evaluation of the effects of tableting speed on the relationships between compaction pressure, tablet tensile strength, and tablet solid fraction. J Pharm Sci 2005;94:465-72.
4. Brazil. RDC N °73, DOU N °67, April 08, 2016. National Health Surveillance Agency–Ministry of Health, Brazil; 2016.
5. ICH. Pharmaceutical Development Q8. ICH Harmonised Tripartite Guideline 2009;8:1-28.
6. Moore CMV. Quality by design–FDA lessons learned and challenges for international harmonization. Int Conf Drug Dev 2012. p. 1-28.
7. S AK, N VG, Dv G, Sivadasu P. Formulation and development of in situ forming gel for the treatment of oral thrush. Asian J Pharm Clin Res 2018;11:342-6.
8. Gupta A, Kumar J, Verma S, Singh H. Application of quality by design approach for the optimization of orodispersible film formulation. Asian J Pharm Clin Res 2018;11:8-11.
9. Guntaka PR, Lankalapalli S. Solubility and dissolution enhancement of ivacaftor tablets by using solid dispersion technique of hot-melt extrusion-a design of experimental approach. Asian J Pharm Clin Res 2019;12:356-63.
10. Khanam N, Alam MI, Md Yusuf Ali QMAI, Siddiqui A. A review on optimization of drug delivery system with experimental designs. Int J Appl Pharm 2018;10:7-12.
11. Chowdary KPR, Shankar KR, Sowjanya VVLSP. Optimization of irbesartan tablet formulation by 23 factorial design. Int J Curr Pharm Sci 2015;7:39-42.
12. Chaudhary SA. DoE/QbD optimization model for "Tablet compression" process using circumscribed central composite RSM. Int J Pharm 2015;486:1-388.
13. Tho I, Bauer Brand LA. Quality by design (QbD) approaches for the compression step of tableting. Expert Opin Drug Delivery 2011;8:1631-44.
14. Haware RV, Tho I, Bauer Brand LA. Application of multivariate methods to compression behavior evaluation of directly compressible materials. Eur J Pharm Biopharm 2009;72:148-55.
15. Lipps MD, Sakr AM. Characterization of wet granulation process parameters using response surface methodology top-spray fluidized bed. J Pharm Sci 1994;83:937-47.
16. Gonnissen Y, Gonçalves SIV, De Geest BG, Remon JP, Veraet C. Process design applied to optimise a directly compressible powder produced via a continuous manufacturing process. Eur J Pharm Biopharm 2008;68:760-70.
17. Garlapati VK, Roy L. Utilization of response surface methodology for modeling and optimization of tablet compression process. J Young Pharm 2017;9:417-21.
18. Iancu V, Roncea F, Cazacincu RG, Lupu CE, Miresan H, Danaila CN, et al. Response surface methodology for optimization of diclofenac sodium orodispersible tablets (odts). Farmacia 2016;64:210-6.
19. Brunton LL, Knollmen B, Hilal Dandan R. The pharmacological basis of therapeutics. 13th ed. New York: McGraw-Hill; 2017.
20. Stat-Ease Design-Expert [software]; 2020. Available from: https://www.statease.com/software/design-expert/ [Last accessed on 18 Nov 2020].
21. Ostertagova E, Ostertag O. Methodology and application of one-way ANOVA. Am J Mech Eng 2013;1:256-61.
22. Brazilian Pharmacopoeia-National Health Surveillance Agency (ANVISA). 5th ed. Brasília; 2010.
23. Khan F, Hossain M, Anika T, Moon SA. Impact of sodium lauryl sulphate on the release of carbamazepine from methocel k15m cr based matrix tablets. Bangladesh Pharm J 2012;15:79-82.
24. Masilungan FC, Kraus KF. Determination of precompression and compression force levels to minimize tablet friability using simplex. Drug Dev Ind Pharm 1989;15:1771-8.
25. Chen L, Chen LZ, Yang XJ, Yu YP. Effects of feed shoe wheel speed on tablet weight variability. Key Eng Mater 2012;492:497-500.
26. Peeters E, De Beer T, Vervaet C, Remon JP. Reduction of tablet weight variability by optimizing paddle speed in the forced feeder of a high-speed rotary tablet press. Drug Dev Ind Pharm 2014;41:530-9.
27. Shipar AH, Wadhwa A, Varughese C, Kaur N, Thayaparan N. Effect of compression force on tablet hardness and disintegration time. MT13-3 Toronto Institute Pharm Technol 2014;5:121-9.
This work is licensed under a Creative Commons Attribution 4.0 International License.