Predicting Drug Substances Autoxidation
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Chemical degradation and stability in formulation is a recurrent issue in pharmaceutical development of drugs. The objective of the present study was to develop an in silico risk assessment of active pharmaceutical ingredients (APIs) stability with respect to autoxidation.
The chemical degradation by autoxidation of a diverse series of APIs has been investigated with molecular modelling tools. A set of 45 organic compounds was used to test and validate the various computational settings. Aiming to devise a methodology that could reliably perform a risk assessment for potential sensibility to autoxidation, different types of APIs, known for their autoxidation history were inspected. To define the level of approximation needed, various density functional theory (DFT) functionals and settings were employed and their accuracy and speed were compared.
The Local Density Approximation (LDA) gave the fastest results but with a substantial deviation (systematic over-estimation) to known experimental values. The Perdew-Burke-Ernzerhof (PBE) settings appeared to be a good compromise between speed and accuracy.
The present methodology can now be confidently deployed in pharmaceutical development for systematic risk assessment of drug stability.
KEY WORDSDegradation Autoxidation Computational chemistry Pharmaceutical DFT
ACKNOWLEDGMENTS AND DISCLOSURES
We wish to express our deep acknowledgement to several individuals for assistance encouragement and advice: Jean-René Authelin, Antonio Guerreiro, Jérome Kieffer, Nicolas Marchand and Guy Rossey for project initiation and scientific inputs.
- 3.Gorman EM, Padden BE, Munson EJ. Stability: Physical and Chemical. 2008; Wiley & Sons Inc. in Gad SC “Preclinical Development handbook: ADME and biopharmaceutical properties” Chapter 16, 545–570Google Scholar
- 4.Florence AT, Attwood D. Physicochemical principles of pharmacy. 5th ed. London: Pharmaceutical Press; 2011.Google Scholar
- 6.Baertschi SW, Pharmaceutical stress testing: predicting drug degradation. Taylor and Françis informa vol 153 Healthcare; 2005Google Scholar
- 7.Guidance for Industry Q1A(R2) Stability testing of new drug substances and products U.S. Department of health and human services food and drug administration, November 2003Google Scholar
- 9.Parr RG, Yang W. Density-functional theory of atoms and molecules. New York: Oxford University Press; 1989.Google Scholar
- 11.P. Harmon and G. Boccardi, Oxidative susceptibility testing, in: S. W. Baertschi, K. M. Alsante, R.R. Red, ed., Pharmaceutical stress testing - predicting drug degradation, Informa, 2011.Google Scholar
- 15.Michael J. S. Dewar,* Eve G. Zoebisch, Eamonn F. Healy, and James J. P. Stewart AM1: A new general purpose quantum mechanical molecular model’ J. Am.Chem.Soc 107, 3902-3909Google Scholar
- 27.Accelrys Software, Inc. Accelrys 2013Google Scholar
- 32.Lewin JL, Cramer CJ. Rapid quantum mechanical models for the computational estimation of C-H bond dissociation energies as a measure of metabolic stability mol. Pharm. 2004;1:128–35.Google Scholar
- 34.Florey ed, Analytical profiles of drug substances Vol 14, New York Academic Press 1985, 59Google Scholar
- 35.Florey ed, Analytical profiles of drug substances Vol 20, New York Academic Press 1991, 405Google Scholar
- 36.Baertschi SW. Pharmaceutical stress testing: predicting drug degradation. Taylor and Françis informa. Healthc. 2005;153:100.Google Scholar
- 37.Florey ed, Analytical profiles of drug substances Vol 18, New York Academic Press 1989; 245Google Scholar
- 39.Sanofi private communicationGoogle Scholar
- 40.Florey ed, Analytical profiles of drug substances Vol 1, New York Academic Press 1972:93Google Scholar