Advertisement

Design of Experiments in Pharmaceutical Development

  • Abhishek S. Dhoot
  • Gasper J. Fernandes
  • Anup Naha
  • Mahalaxmi Rathnanand
  • Lalit KumarEmail author
Article
  • 2 Downloads

In order to develop high-quality pharmaceutical products, a traditional approach based the univariate or trial and error method was used in the past that led to several problems like non-reproducible, high-cost, and time consuming methods. To overcome these drawbacks, a new concept of the Design of Experiment (DoE) was introduced. DoE is a statistical element of the Quality by Design (QbD) approach introduced by British statistician Sir Ronald Fisher in 1925. The basic objectives of DoE are screening, optimization, and robustness. It involves the execution of experimental design on the basis of suitable variables along with statistical evaluation of obtained responses and exploration of the design space using mathematical or graphical approach. The statistical evaluation empowers to build up the quality of finished products and helps to meet the increasing demands for product of superior quality and standards. This article mainly focuses on the applications of DoE in pharmaceutical product development along with its objectives, design, and selection criteria.

Keywords

Design of Experiment (DoE) Quality by Design (QbD) design pharmaceutical product development 

References

  1. 1.
    A. A. Hald, History of Mathematical Statistics from 1750 to 1930, Wiley Series in Probability and Statistics, Edinburgh – New York (1998).Google Scholar
  2. 2.
    R. A. Fisher, Statistical Methods for Research Workers, Oliver and Boyd, London (1925).Google Scholar
  3. 3.
    R. A. Fisher, J. Min. Agric. Gr. Brit.,33, 503 – 513 (1926).Google Scholar
  4. 4.
    R. A. Fisher, The Design of Experiments, Hafner Publishing Company, Inc., New York (1935).Google Scholar
  5. 5.
    S. N. Politis, P. Colombo, G. Coxlombo, et al., Drug Develop. Ind. Pharm.,43, 889 – 901 (2017).CrossRefGoogle Scholar
  6. 6.
    Design of Experiments for Formulation Development. Pharmaceutical Technology (2005) [cited May 30, 2018]. Available from: http: // www.pharmtech.com/design-experiments-formulation-development-0?id=&sk=&date=&%0A%09%09%09& pageID=22 (Accessed June 20, 2018).
  7. 7.
    A. G. Mirani and V. B. Patravale, Design of experiments: Basic concepts and its application in pharmaceutical product development, in: Pharmaceutical Product Development, (Eds.:V. B. Patravale, J. I. Disouza, and M. T. Rustomjee), CRC Press – Taylor & Francis Group, New York (2016).Google Scholar
  8. 8.
    J. M. Juran, Juran on Quality by Design: the New Steps for Planning Quality into Goods and Services, Free Press, New York (1992).Google Scholar
  9. 9.
    U. S. Food and Drug Administration (2017). Final report from the FDA-EMA pilot program for the parallel assessment of quality-by-design elements of marketing applications. Available at: https: //wayback.archive-it.org/7993/ 20180125055008/https://www.fda.gov/Drugs/DevelopmentApprovalProcess/Manufacturing/ucm552716.htm (Accessed June 16, 2018).
  10. 10.
    B. Shah, D. Khunt, H. Bhatt, et al., Eur. J. Pharm. Sci.78, 54 – 66 (2015).CrossRefGoogle Scholar
  11. 11.
    I. M. Savic, V. D. Marinkovic, L. Tasic, et al., Accred. Qual. Assur.,17, 627 – 33 (2012).CrossRefGoogle Scholar
  12. 12.
    ICH Q8 (R2) Pharmaceutical Development, Guidelines (2009). Available at: https: // www.ich.org/fileadmin/Public_Web_Site/ICH Products/Guidelines/Quality/Q8 R1/Step4/Q8_R2_Guideline. pdf (Accessed July 8, 2018).
  13. 13.
    L. Zhang and S. Mao, Asian J. Pharm. Sci.,12, 1 – 8 (2017).CrossRefGoogle Scholar
  14. 14.
    H. Guo and A. Mettas, Design of Experiments and Data Analysis, in Proceedings of Reliability and Maintainability Symposium (San Jose, CA, USA, 2010). Available at: https: //www.scribd.com/document/261112587/2010-RAMS-Doeand-Data-Analysis (Accessed July 11, 2018).
  15. 15.
    E. Marlowe, R. F. Shangraw, J. Pharm. Sci., 56, 498 – 504 (1967).CrossRefGoogle Scholar
  16. 16.
    D. Granato and V. M. de Araújo Calado, The use and importance of design of experiments (DoE) in process modelling in food science and technology, in: Mathematical and Statistical Methods in Food Science and Technology (D. Granato, ed.), John Wiley & Sons, Inc., New York (2013), pp. 1 – 18.Google Scholar
  17. 17.
    S. Fontdecaba, P. Grima, and X. Tort-Martorell, The Am. Statistic,.68, 205 – 211 (2014).CrossRefGoogle Scholar
  18. 18.
    R. R. Jivani, C. N. Patel, and N. P. Jivani, Indian J. Pharm. Sci.,74, 302 – 311 (2012).CrossRefGoogle Scholar
  19. 19.
    N. A. Charoo, A. A. Shamsher, A. S. Zidan, et al., Int. J. Pharm.,423, 167 – 78 (2012).CrossRefGoogle Scholar
  20. 20.
    M. Naeem, N. U. R. Rahman, J. A. Khan, et al., Lat. Am. J. Pharm.,32, 1196 – 1204 (2013).Google Scholar
  21. 21.
    N. Patel, S. Jain, P. Madan, et al., Drug Develop. Ind. Pharm.,42, 1894 – 1902 (2016).CrossRefGoogle Scholar
  22. 22.
    M. A. Badawi and L. K. El-Khordagui, Eur. J. Pharm. Sci.,58, 44 – 54 (2014).CrossRefGoogle Scholar
  23. 23.
    J. Kushner, B. A. Langdon, I. Hicks, et al., J. Pharm. Sci.,103, 527 – 538 (2013).CrossRefGoogle Scholar
  24. 24.
    P. M. Kumar and A. Ghosh, Eur. J. Pharm. Sci.,96, 243 – 254 (2017).CrossRefGoogle Scholar
  25. 25.
    E. Sánchez-López, M. A. Egea, A. Cano, et al., Colloid Surf. Biointerfaces, 145, 241 – 250 (2016).CrossRefGoogle Scholar
  26. 26.
    L. Kumar, M. S. Reddy, R. S. Managuli, et al., Saudi Pharm. J.,23, 549 – 555 (2015).CrossRefGoogle Scholar
  27. 27.
    N. S. K. Srinivas, R. Verma, G. P. Kulyadi, et al., Int. J. Nanomed.,12, 15 – 28 (2017).CrossRefGoogle Scholar
  28. 28.
    G. N. Ferreira, M. G. R. Silva, A. G. M. Fraga, et al., Braz. J. Pharm. Sci.,50, 291 – 300 (2014).CrossRefGoogle Scholar
  29. 29.
    P. Panzade, G. Shendarkar, S. Shaikh, et al., Adv. Pharm. Bull.,7, 399 – 408 (2017).CrossRefGoogle Scholar
  30. 30.
    E. Maretti, C. Rustichelli, M. Romagnoli, et al., Int. J. Pharm.,511, 669 – 679 (2016).CrossRefGoogle Scholar
  31. 31.
    M. H. Shariare, M. de Matas, P. York, et al., Int. J. Pharm.,408, 58 – 66 (2011).CrossRefGoogle Scholar
  32. 32.
    M. Malladi and R. Jukanti. J. Drug Deliver. Sci. Technol.,35, 134 – 145 (2016).CrossRefGoogle Scholar
  33. 33.
    M. S. Reddy, L Kumar, Z. Attari, et al., Indian J. Pharm. Sci.,79, 16 – 28 (2017).Google Scholar
  34. 34.
    P. F. Chavez, P. Lebrun, P. Y. Sacréet, et al., Int. J. Pharm.,486(1 – 2), 13 –20 (2015).CrossRefGoogle Scholar
  35. 35.
    S. I. Badawy, A. S. Narang, K. R. LaMarche, et al., J. Pharm. Sci.,105(1), 168 – 81 (2016).CrossRefGoogle Scholar
  36. 36.
    T. Tol, N. Kadam, N. Raotole, et al., J. Chromatogr., 1432, 26 – 38 (2016).CrossRefGoogle Scholar
  37. 37.
    B. Gu and D. J. Burgess, Int. J. Pharm.,495(1), 393 – 403 (2015).CrossRefGoogle Scholar
  38. 38.
    A. Al-Gheethi, E. Noman, R. M. S. Radin Mohamed, et al. J. Hazard. Mater., 365, 883 – 894 (2019).CrossRefGoogle Scholar
  39. 39.
    M. Sakr, R. Hanafi, M. Fouad, et al. Spectrochim. Acta Mol. Biomol. Spectrosc., 208, 114 – 123 (2019).CrossRefGoogle Scholar
  40. 40.
    A. Nair, D. Khunt, and M. Misra. Powder Technol., 342, 156 – 65 (2019).CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Abhishek S. Dhoot
    • 1
  • Gasper J. Fernandes
    • 1
  • Anup Naha
    • 1
  • Mahalaxmi Rathnanand
    • 1
  • Lalit Kumar
    • 1
    Email author
  1. 1.Department of Pharmaceutics, Manipal College of Pharmaceutical SciencesManipal Academy of Higher EducationUdupiIndia

Personalised recommendations