Routine screening for the presence of adulteration in raw materials using automated nuclear magnetic resonance spectroscopy

PDA J Pharm Sci Technol. 2012 Nov-Dec;66(6):547-59. doi: 10.5731/pdajpst.2012.00890.

Abstract

In an effort to increase the security of the supply chain for raw materials used in the manufacture of human therapeutics, a routine screen to detect the presence of adulteration using fully automated nuclear magnetic resonance spectroscopy has been developed and qualified for use in quality control laboratories. The method involves the collection of one-dimensional (1)H and (13)C spectra, which are subsequently processed to identify and quantitate raw material constituents by comparison to a spectral database. The resulting method is an easy-to-use limit test that can automatically determine the integrity of incoming raw materials. The method is intended to be used in good manufacturing practice production facilities and is suitable for excipients and aqueous soluble raw materials used in biopharmaceutical processes.

Lay abstract: In an effort to increase the security of the supply chain for raw materials used in the manufacture of human therapeutics, a routine screen to detect the presence of adulteration using fully automated nuclear magnetic resonance (NMR) spectroscopy has been developed and qualified for use in quality control laboratories. The method involves the collection of NMR spectra, which are subsequently processed to identify and quantitate raw material constituents by comparison to a spectral database. The resulting method is an easy-to-use limit test that can automatically determine the integrity of incoming raw materials. The method is intended to be used in good manufacturing practice production facilities and is suitable for excipients and aqueous soluble raw materials used in biopharmaceutical processes.

MeSH terms

  • Drug Contamination* / prevention & control
  • Humans
  • Magnetic Resonance Imaging
  • Magnetic Resonance Spectroscopy*
  • Nuclear Magnetic Resonance, Biomolecular
  • Pattern Recognition, Automated
  • Quality Control