Predictive and Accelerated Formulation Design Using Synchrotron Methods

Abstract

Predictive formulation design and accelerated formulation design can lead to the discovery of useful formulations to support drug clinical studies and successful drug approval. Predictive formulation design can also lead to discovery of a path for commercialization, especially for poorly soluble drugs, when the target product profile is well defined and a “learning before doing” approach is implemented. One of the key components of predictive/accelerated formulation design is to understand and leverage the material properties of drug substance including solubility, BCS classification, polymorphs, salt formation, amorphous form, amorphous complex, and stability. In addition, utilizing synchrotron-based PDF (pair distribution function) analysis can provide important structural information for the formulation. This knowledge allows control of physical and chemical stability of the designed product. Finally, formulation design should link to process development following Quality by Design principles, and solid-state chemistry should play a critical role in many of the steps required to achieve Quality by Design, which can lead to successful product development.

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References

  1. 1.

    Pisano GP. Development factory: unlocking the potential of process innovation. Harvard Business School Press; 1996.

  2. 2.

    Yalkowski S. Solubility and solubilization in aqueous media. American Chemical Society; 1999.

  3. 3.

    Oh DM, Curl RL, Amidon GL. Estimating the fraction dose absorbed from suspensions of poorly soluble compounds in humans: a mathematical model. Pharm Res. 1992;10:264–70.

    Article  Google Scholar 

  4. 4.

    Ku MS. Use of the biopharmaceutical classification system in early drug development. AAPS J. 2008;10:208–12.

    CAS  Article  Google Scholar 

  5. 5.

    Guttman D, Higuchi T. Possible complex formation between macromolecules and certain pharmaceuticals. X. The interaction of some phenolic compounds with polyethylene glycols, polypropylene glycols, and polyvinylpyrrolidone. J Am Pharm Assoc Am Pharm Assoc. 1956;45:659–64.

    CAS  Article  Google Scholar 

  6. 6.

    Laitinen R, et al. Supersaturating drug delivery systems: the potential of co-amorphous drug formulations. Int J Pharm (Amsterdam, Neth). 2017;532:1–12.

    CAS  Google Scholar 

  7. 7.

    Chaven RB, Thipparaboina R, Kumar D, Shastri NR. Co amorphous systems: a product development perspective. Int J Pharm (Amsterdam, Neth). 2016;515:403–15.

    Google Scholar 

  8. 8.

    Kasten G, Grohaganz H, Rades T, Lobmann K. Development of a screening method for co-amorphous formulations of drugs and amino acids. Eur J Pharm Sci. 2016;95:28–35.

    CAS  Article  Google Scholar 

  9. 9.

    Dengale SJ, Grohganz H, Rades T, Lobmann K. Recent advances in co-amorphous drug formulations. Adv Drug Deliv Rev. 2016;100:116–25.

    CAS  Article  Google Scholar 

  10. 10.

    Yi T, Wan J, Xu X, Yang X. A new solid self-microemulsifying formulation prepared by spray-drying to improve the oral bioavailability of poorly water soluble drugs. Eur J Pharm Biopharm. 2008;70:439–44.

    CAS  Article  Google Scholar 

  11. 11.

    Balakrishnan P, Lee BJ, Oh DH, Kim JO, Hong MJ, Jee JP, et al. Enhanced oral bioavailability of dexibuprofen by a novel solid self-emulsifying drug delivery system (SEDDS). Eur J Pharm Biopharm. 2009;72:539–45.

    CAS  Article  Google Scholar 

  12. 12.

    Kanzer J, Hupfeld S, Vasskog T, Tho I, Hölig P, Mägerlein M, et al. In situ formation of nanoparticles upon dispersion of melt extrudate formulations in aqueous medium assessed by asymmetrical flow field-flow fractionation. J Pharm Biomed Anal. 2010;53:359–65. https://doi.org/10.1016/j.jpba.2010.04.012.

    CAS  Article  PubMed  Google Scholar 

  13. 13.

    Tho I, Liepold B, Rosenberg J, Maegerlein M, Brandl M, Fricker G. Formation of nano/micro-dispersions with improved dissolution properties upon dispersion of ritonavir melt extrudate in aqueous media. Eur J Pharm Sci. 2010;40:25–32. https://doi.org/10.1016/j.ejps.2010.02.003.

    CAS  Article  PubMed  Google Scholar 

  14. 14.

    Benmore CJ, Weber JKR, Tailor AN, Cherry BR, Yarger JL, Mou Q, et al. Structural characterization and aging of glassy pharmaceuticals made using acoustic levitation. J Pharm Sci. 2013;102:1290–300. https://doi.org/10.1002/jps.23464.

    CAS  Article  PubMed  Google Scholar 

  15. 15.

    Terban MW, Johnson M, Di Michiel M, Billinge SJL. Detection and characterization of nanoparticles in suspension at low concentrations using the X-ray total scattering pair distribution function technique. Nanoscale. 2015;7:5480–7. https://doi.org/10.1039/C4NR06486K.

    CAS  Article  PubMed  Google Scholar 

  16. 16.

    Kuentz M. Drug absorption modeling as a tool to define the strategy in clinical formulation development. AAPS J. 2008;10:473–9.

    CAS  Article  Google Scholar 

  17. 17.

    Doyon L, Tremblay S, Bourgon L, Wardrop E, Cordingley M. Selection and characterization of HIV-1 showing reduced susceptibility to the non-peptidic protease inhibitor tipranavir. Antivir Res. 2005;68:27–35.

    CAS  Article  Google Scholar 

  18. 18.

    Matsuda Y, Tatsumi E. Physiochemical characterization of furosemide modifications. Int J Pharm. 1990;60:11–26.

    CAS  Article  Google Scholar 

  19. 19.

    Chen S, Sheikh AY, Ho R. Evaluation of effects of pharmaceutical processing on structural disorders of active pharmaceutical ingredient crystals using nanoindentation and high-resolution total scattering pair distribution function analysis. J Pharm Sci. 2014;103:3879–90. https://doi.org/10.1002/jps.24178.

    CAS  Article  PubMed  Google Scholar 

  20. 20.

    Docherty R, Kougoulos T, Horspool K. Materials science and crystallization: the interface of drug substance and drug product. Am Pharm Rev. 2009;12:34.

    CAS  Google Scholar 

  21. 21.

    Hu Y, Wikstron H, Byrn SR, Taylor L s. Estimation of the transition temperature for an enantiotropic polymorphic system from the transformation kinetics monitored using Raman spectroscopy. J Pharm Biomed Anal. 2007;45:546–51.

    CAS  Article  Google Scholar 

  22. 22.

    Byrn SR, Zografi G, Chen X. Accelerating proof of concept for small molecule drugs using solid-state chemistry. J Pharm Sci. 2010;99:3665–75. https://doi.org/10.1002/jps.22215.

    CAS  Article  PubMed  Google Scholar 

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Correspondence to Stephen R. Byrn.

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Guest Editors: Ajaz S. Hussain, Kenneth Morris, and Vadim J. Gurvich

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Byrn, S.R., Chen, X.S. & Smith, P.A. Predictive and Accelerated Formulation Design Using Synchrotron Methods. AAPS PharmSciTech 20, 176 (2019). https://doi.org/10.1208/s12249-019-1375-2

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KEY WORDS

  • formulation
  • quality
  • synchrotron
  • x-ray
  • accelerated