Preview

Russian Journal of Biotherapy

Advanced search

Optimization of wet granulation by surface response method in obtaining GSB-106 tablets

https://doi.org/10.17650/1726-9784-2025-24-3-53-62

Abstract

Background. A key component of pharmaceutical development is the optimization and justification of technological processes, since the influence of critical process parameters (KPP) on critical quality indicators (CPC) is one of the dimensions of the design field within which a medicinal product (LP) is created. This study shows the relationship between the conditions of wet granulation and the characteristics of GSB-106 tablets.

Aim. To study the effect of wet granulation PPC on the main parameters of GSB-106 tablets in the development of an optimal technological regime using the Box–Behnken plan.

Materials and methods. Equipment used: high-speed mixer granulator GSL-12 (Etorch, China), granulator with screening function WG-30 (Pharmag, Germany); manual hydraulic press PRG-50 (Russia); strength analyzer TBF 1000 (Copley Scientific, UK); disintegration analyzer SVM 221 (Erweka, Germany); PTF 3DR abrasion analyzer

(Pharma Test, Germany). The mathematical planning of the experiment was carried out using the surface response method with a three-level Box–Behnken plan, regression and variance analysis were applied, and multi-criteria optimization using generalized desirability by Derringer–Suich.

Results. To develop the technological process, 15 experiments were conducted in the entire range of varying factors, such as the duration of mixing, the speed of rotation of the blades, and the amount of granulating solution. The following pharmaceutical and technological characteristics were studied: crushing strength and disintegration of tablets at a pressing pressure of 5 kN / m2, 10 kN / m2, as well as abrasion resistance. Based on the data obtained, regression analysis equations were developed for each studied characteristic, the obtained models were compared by determination coefficients, the statistical significance of the equation terms was evaluated, and regression equations were optimized by getting rid of statistically insignificant equation terms. After constructing a mathematical model with adequate predictive ability, multi-criteria optimization was performed using generalized Derringer–Suich desirability.

Conclusion. Multi-criteria optimization allowed us to determine the most optimal combination of control factors in accordance with the prioritization of the desirability of pharmaceutical and technological characteristics. The identified optimal technological regime consists in adding 68.69 ml of purified water and stirring the tablet mixture for 9.92 minutes at a speed of a paddle mixer for 200 rpm, which provide the most optimal pharmaceutical and technological characteristics of the tablets.

About the Authors

Sergey V. Tishkov
Federal Research Center for Innovator and Emerging Biomedical and Pharmaceutical Technologies
Russian Federation

Sergey Valerievich Tishkov 

8 Baltiyskaya St., Moscow 125315



Evgenia V. Blynskaya
Federal Research Center for Innovator and Emerging Biomedical and Pharmaceutical Technologies
Russian Federation

8 Baltiyskaya St., Moscow 125315



Konstantin V. Alekseev
Federal Research Center for Innovator and Emerging Biomedical and Pharmaceutical Technologies
Russian Federation

8 Baltiyskaya St., Moscow 125315



Vladimir L. Dorofeev
Federal Research Center for Innovator and Emerging Biomedical and Pharmaceutical Technologies
Russian Federation

8 Baltiyskaya St., Moscow 125315



References

1. ICH Q8. International Conference on Harmonization (ICH) of Technical Requirements for Registration of Pharmaceuticals for Human Use. Geneva, 2005. P. 19.

2. Quality risk management (ICH Q9). EMA/INS/ GMP/79766/2011. URL: http://www.emea.europa.eu/docs/en_GB/document_library/Scientific_guideline/2009/09/WC500002873.pdf.

3. Tishkov S.V., Blynskaja E.V., Alekseev K.V. et al. Using the SeDeM-ODT method for the development of GK-2 tablets dispersed in the oral cavity. Rossijskij bioterapevticeskij zurnal = Russian Journal of Biotherapy 2021;20(3):34–46. (In Russ.). DOI: 10.17650/1726-9784-2021-20-3-34-46

4. Tishkov S.V., Blynskaja E.V., Alekseev K.V. et al. Optimization of the technology of pressing tablets of GK-2hexamethyleneamide bis-(N-monosuccinyl-L-glutamyl-Llysine), dispersible in the oral cavity, using mathematical models of Heckel and Kawakite. Khimiko-farmatsevticheskiy zhurnal = Pharmaceutical Chemistry Journal 2021;55(12):38–42. (In Russ.). DOI: 10.30906/0023-1134-2021-55-12-38-42

5. Holm P., Schaefer T., Larsen C. End-point detection in a wet granulation process. Pharm Dev Technol 2001;6(2):181–92. DOI: 10.1081/pdt-100000739

6. Rajniak P., Mancinelli C., Chern R.T. et al. Experimental study of wet granulation in fluidized bed: impact of the binder properties on the granule morphology. Int J Pharm 2007;334(1-2):92–102. DOI: 10.1016/j.ijpharm.2006.10.040

7. Iveson S.M., Litster J.D., Hapgood K. et al. Nucleation, growth and breakage phenomena in agitated wet granulation processes: a review. Powder Technol 2001;117(1-2):3–39. DOI: 10.1016/S0032-5910(01)00313-8

8. Iveson S.M., Wauters P.A., Forrest S. et al. Growth regime map for liquid-bound granules: further development and experimental validation. Powder Technol 2001;117(1-2):83–97. DOI: 10.1016/S0032-5910(01)00317-5

9. De Simone V., Dalmoro A., Lamberti G. et al. Central composite design in HPMC granulation and correlations between product properties and process parameters. New J Chem 2017;41(14):6504–13. DOI: 10.1039/C7NJ01280B

10. Chitu T.M., Oulahna D., Hemati M. Wet granulation in laboratory scale high shear mixers: Effect of binder properties. Powder Technol 2011;206(1-2):25–33. DOI: ff10.1016/j.powtec.2010.07.012

11. Litster J.D., Hapgood K.P., Michaels J.N. et al. Liquid distribution in wet granulation: dimensionless spray flux. Powder Technol 2001;114(1-3):32–9. DOI: 10.1016/S0032-5910(00)00259-X

12. Blynskaja E.V., Bueva V.V., Alekseev K.V. et al. Evaluation of the size and shape of GSB-106 granules obtained by wet granulation using image analysis method. Voprosy obespechenija kachestva lekarstvennyh sredstv = Journal of Pharmaceuticals Quality Assurance Issue 2021;2(32):47–53. (In Russ.) DOI: 10.34907/JPQAI.2021.71.82.007

13. Seredenin S.B., Voronina T.A., Gudasheva T.A. et al. Antidepressant effect of the original low molecular weight BDNF mimetic, dimeric dipeptide GSB-106. Acta Naturae (russkojazychnaja versija) 2013;4(19):116–20. (In Russ.).

14. Beg S., Akhter S. Box–Behnken designs and their applications in pharmaceutical product development. Design of Experiments for Pharmaceutical Product Development. Vol. I: Basics and Fundamental Principles. Springer, 2021. P. 77–85.

15. Blynskaja E.V. Bueva, V.V., Alekseev, K.V. et al. Harrington’s Desirability Function in the Development of the GSB-106 Tablet Composition. Voprosy obespechenija kachestva lekarstvennyh sredstv = Journal of Pharmaceuticals Quality Assurance Issue 2019;26(4):57–65. (In Russ.).


Review

For citations:


Tishkov S.V., Blynskaya E.V., Alekseev K.V., Dorofeev V.L. Optimization of wet granulation by surface response method in obtaining GSB-106 tablets. Russian Journal of Biotherapy. 2025;24(3):53-62. (In Russ.) https://doi.org/10.17650/1726-9784-2025-24-3-53-62

Views: 54


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


ISSN 1726-9784 (Print)
ISSN 1726-9792 (Online)