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Developments in formulation analyses by powder diffraction analysis

  • T. G. Fawcett (a1), J. Faber (a1), F. Needham (a1), S. N. Kabekkodu (a1), C. R. Hubbard (a2) and J. A. Kaduk (a3)...


Developments in X-ray analysis hardware and software have combined to dramatically improve the throughput, speed, and accuracy of formulation analyses. We will focus on a complimentary development, the growth and application of a comprehensive database based on the Powder Diffraction File™ (PDF®). The PDF is an edited and standardized combination of several crystallographic databases with ∼497 000 published entries. The comprehensive nature of this database, combined with phase identification and digital pattern simulations, was used to identify complex formulations with crystalline and noncrystalline ingredients. We will show how these parallel developments enhance the ability to correctly identify complex formularies.


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Faber, J. (2004). “ICDD’s New PDF-4 Organics Database: Search Indexes, Full Pattern Analysis and Data Mining,” Crystallogr. Rev. CRRVEN 10, 97107.
Fawcett, T. G., Faber, J., and Hubbard, C. R. (2004). “Formulation Analysis of Off-the-Shelf Pharmaceuticals,” Am. Pharm. Rev. 7(3), 8083.
Gilmore, C. J., Barr, G., and Dong, W. (2004a). “High throughput powder diffraction. II. Applications of clustering methods and multivariate data analysis,” J. Appl. Crystallogr. JACGAR 37, 243252.
Gilmore, C. J., Barr, G., Dong, W., and Faber, J. (2004b). “High throughput powder diffraction. III. The application of full profile pattern matching and multivariate statistical analysis to round robin type data sets,” J. Appl. Crystallogr. JACGAR 37, 635642.
Kabekkodu, S. N., Faber, J., and Fawcett, T. G. (2002). “New Powder Diffraction File (PDF-4) in relational database format: Advantages and data-mining capabilities,” Acta Crystallogr. ASBSDK 10.1107/S0108768102002458 58, 333337.
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Powder Diffraction
  • ISSN: 0885-7156
  • EISSN: 1945-7413
  • URL: /core/journals/powder-diffraction
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