posted on 2021-07-08, 12:39authored byAlon Grinberg Dana, Haoyang Wu, Duminda S. Ranasinghe, Frank C. Pickard, Geoffrey P. F. Wood, Todd Zelesky, Gregory W. Sluggett, Jason Mustakis, William H. Green
Stress testing of active pharmaceutical
ingredients (API) is an
important tool used to gauge chemical stability and identify potential
degradation products. While different flavors of API stress testing
systems have been used in experimental investigations for decades,
the detailed kinetics of such systems as well as the chemical composition
of prominent reactive species, specifically reactive oxygen species,
are unknown. As a first step toward understanding and modeling API
oxidation in stress testing, we investigated a typical radical “soup”
solution an API is subject to during stress testing. Here we applied ab initio electronic structure calculations to automatically
generate and refine a detailed chemical kinetics model, taking a fresh
look at API oxidation. We generated a detailed kinetic model for a
representative azobis(isobutyronitrile) (AIBN)/H2O/CH3OH stress-testing system with a varied cosolvent ratio (50%/50%–99.5%/0.5%
vol water/methanol) for 5.0 mM AIBN and representative pH values of
4–10 at 40 °C that was stirred and open to the atmosphere.
At acidic conditions, hydroxymethyl alkoxyl is the dominant alkoxyl
radical, and at basic conditions, for most studied initial methanol
concentrations, cyanoisopropyl alkoxyl becomes the dominant alkoxyl
radical, albeit at an overall lower concentration. At acidic conditions,
the levels of cyanoisopropyl peroxyl, hydroxymethyl peroxyl, and hydroperoxyl
radicals are relatively high and comparable, while, at both neutral
and basic pH conditions, superoxide becomes the prominent radical
in the system. The present work reveals the prominent species in a
common model API stress testing system at various cosolvent and pH
conditions, sets the stage for an in-depth quantitative API kinetic
study, and demonstrates the usage of novel software tools for automated
chemical kinetic model generation and ab initio refinement.