Skip to main content
Log in

Polymorphic and Covalent Transformations of Gabapentin in Binary Excipient Mixtures after Milling-Induced Stress

  • Research Paper
  • Theme: Formulation and Manufacturing of Solid Dosage Forms
  • Published:
Pharmaceutical Research Aims and scope Submit manuscript

Abstract

Purpose

The purpose of the research described herein was to develop a kinetic model for quantifying the effects of conditional and compositional variations on non-covalent polymorphic and covalent chemical transformations of gabapentin.

Methods

Kinetic models that describe the relationship between polymorphs and degradation product in a series of sequential or parallel steps were devised based on analysis of the resultant concentration time profiles. Model parameters were estimated using non-linear regression and Bayesian methods and evaluated in terms of their quantitative relationship to compositional and conditional variations.

Results

The model was constructed in which co-milling gabapentin with excipients determined three physically-initial concentrations (II0*, II0 and III0) and one chemically-initial concentration (lactam0). For chemical transitions, no humidity effect was present but the catalytic effects of excipients on the conversion of II and III➔lactam were observed. For physical transition, excipient primarily influenced the physical state transition of III➔II through its ability to interact with humidity.

Conclusions

This model was shown to be robust to quantitatively account for the effects of temperature, humidity and excipient on rate constants associated with kinetics for each physical and chemical transition.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

Abbreviations

II0 :

Initial concentration of gabapentin Form II

II0 * :

Estimated initial concentration of physically-disordered gabapentin Form II

III0 :

Initial concentration of gabapentin Form III

II➔III:

Physical state transition of gabapentin Form II➔III

II*➔II:

Physical state transition of physically-disordered gabapentin Form II*➔II

III➔II:

Physical state transition of gabapentin Form III➔II

II➔lactam:

Chemical degradation of gabapentin Form II➔lactam

II*➔lactam:

Chemical degradation of physically-disordered gabapentin Form II*➔lactam

III➔lactam:

Chemical degradation of gabapentin Form III➔lactam

AMASTK:

R-language based Advanced Modeling and Simulation Tool Kit

β:

Humidity sensitivity term in modified Arrhenius equation

13C CP/MAS NMR:

13C cross-polarization/magic angle spinning nuclear magnetic resonance

CaHPO4 :

Dibasic calcium phosphate dihydrate

Form II or II:

Gabapentin Form II

Form II* or II*:

Physically-disordered gabapentin Form II

Form III or III:

Gabapentin Form III

1H T1 :

Proton relaxation time in laboratory frame

HPC:

Hydroxy propyl cellulose

HPLC:

High-performance liquid chromatography

k1 :

Estimated rate constant for conversion of II*➔II

k2 :

Estimated rate constant for rapid conversion of II*➔lactam

k3 :

Estimated rate constant for the conversion of II➔lactam

k4 :

Estimated rate constant for the conversion of III➔lactam

k5 :

Estimated rate constant for polymorphic transformation of III➔II

lactam or L:

Gabapentin-lactam

Lactam0 or L0 :

Initial concentration of gabapentin-lactam

MCMC:

Markov Chain Monte Carlo

SiO2 :

Colloidal silicon dioxide

References

  1. Dempah KE, Barich DH, Kaushal AM, Zong Z, Desai SD, Suryanarayanan R, et al. Investigating gabapentin polymorphism using solid-state NMR spectroscopy. AAPS PharmSciTech. 2013;14(1):19–28.

    Article  CAS  PubMed  Google Scholar 

  2. Lin SY, Hsu CH, Ke WT. Solid-state transformation of different gabapentin polymorphs upon milling and co-milling. Int J Pharm. 2010;396(1–2):83–90.

    Article  CAS  PubMed  Google Scholar 

  3. Zong Z, Desai SD, Kaushal A, Barich D, Huang H-S, Munson E, et al. The stabilizing effect of moisture on the solid-state degradation of gabapentin. AAPS PharmSciTech. 2011;12(3):924–31.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Reece HA, Levendis DC. Polymorphs of gabapentin. Acta Crystallogr Sect C: Cryst Struct Commun. 2008;C64(3):o105–8.

    Article  Google Scholar 

  5. Zong Z, Qiu J, Tinmanee R, Kirsch L. Kinetic model for solid-state degradation of gabapentin. J Pharm Sci. 2012;101(6):2123–33.

    Article  CAS  PubMed  Google Scholar 

  6. Tinmanee R, Larsen S, Morris K, Kirsch L. Quantification of gabapentin polymorphs in gabapentin/excipient mixtures using solid state 13C NMR spectroscopy and X-ray powder diffraction. J Pharm Biomed Anal. 2017;146(29–36).

  7. Braga D, Grepioni F, Maini L, Rubini K, Polito M, Brescello R, et al. Polymorphic gabapentin: thermal behaviour, reactivity and interconversion of forms in solution and solid-state. New J Chem. 2008;32(10):1788–95.

    Article  CAS  Google Scholar 

  8. Soetaert K, Petzoldt T, Setzer W. Solving differential equations in R: Package deSolve. J Stat Softw. 2010;33(9):1–25.

    Article  Google Scholar 

  9. Soetaert K, Petzoldt T. Inverse modelling, sensitivity and Monte Carlo analysis in R using package FME. J Stat Softw. 2010;33(3):1–28.

    Article  Google Scholar 

  10. Blau G, Lasinski M, Orcun S, Hsu S-H, Caruthers J, Delgass N, et al. High fidelity mathematical model building with experimental data: A Bayesian approach. Comput Chem Eng. 2008;32(4–5):971–89.

    Article  CAS  Google Scholar 

  11. Nash J. On best practice optimization methods in R. J Stat Softw. 2014;60(2):1–14.

    Article  Google Scholar 

  12. Metropolis N, Rosenbluth AW, Rosenbluth MN, Teller AH, Teller E. Equation of state calculations by fast computing machines. J Chem Phys. 1953;21(6):1087–92.

    Article  CAS  Google Scholar 

  13. Hastings WK. Monte Carlo sampling methods using Markov chains and their applications. Biometrika. 1970;57(1):97–109.

    Article  Google Scholar 

  14. Brooks SP. Bayesian computation: a statistical revolution. Philos Trans A Math Phys Eng Sci. 2003;361(1813):2681–97.

    Article  PubMed  Google Scholar 

  15. Hao YJ, Tanaka T. Role of the contact points between particles on the reactivity of solid. Can J Chem Eng. 1988;66(5):761–6.

    Article  CAS  Google Scholar 

  16. Qiu Z, Stowell JG, Cao W, Morris KR, Byrn SR, Carvajal MT. Effect of milling and compression on the solid-state maillard reaction. J Pharm Sci. 2005;94(11):2568–80.

    Article  CAS  PubMed  Google Scholar 

  17. Qiu Z, Stowell JG, Morris KR, Byrn SR, Pinal R. Kinetic study of the Maillard reaction between metoclopramide hydrochloride and lactose. Int J Pharm. 2005;303(1–2):20–30.

    Article  CAS  PubMed  Google Scholar 

  18. Zografi G. States of water associated with solids. Drug Dev Ind Pharm. 1988;14(14):1905–26.

    Article  CAS  Google Scholar 

  19. Thakral NK, Ragoonanan V, Suryanarayanan R. Quantification, mechanism, and mitigation of active ingredient phase transformation in tablets. Mol Pharm. 2013;10(8):3128–36.

    Article  CAS  PubMed  Google Scholar 

  20. Yoshinari T, Forbes RT, York P, Kawashima Y. Moisture induced polymorphic transition of mannitol and its morphological transformation. Int J Pharm. 2002;247(1–2):69–77.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgments and Disclosures

Special thanks are given to the University of Iowa Central Nuclear Magnetic Resonance Facility.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Lee E. Kirsch.

Additional information

Guest Editors: Tony Zhou and Tonglei Li

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Tinmanee, R., Stamatis, S.D., Ueyama, E. et al. Polymorphic and Covalent Transformations of Gabapentin in Binary Excipient Mixtures after Milling-Induced Stress. Pharm Res 35, 39 (2018). https://doi.org/10.1007/s11095-017-2285-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11095-017-2285-1

KEY WORDS

Navigation