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 azobisisobutyronitrile (AIBN)/H 2 O/CH 3 OH stress-testing system with varied co-solvent ratio (50%/50% --99.5%/0.5% vol. water/methanol) and for representative pH values (4--10) at 40oC 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 co-solvent and pH conditions, sets the stage for an in-depth quantitative API kinetic study, and demonstrates usage of novel software tools for automated chemical kinetic model generation and ab-initio refinement. File list (2) download file view on ChemRxiv 2021.04.01 a The Soup.pdf (5.01 MiB) download file view on ChemRxiv 2021.01.29 a Soup SI.pdf (1.02 MiB)

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Gauging the chemical stability of active pharmaceutical ingredients (APIs) is critical at various stages of pharmaceutical development to identify potential risks from drug degradation and ensure the quality and safety of the drug product. Stress testing has been the major experimental method to study API stability, but this analytical approach is time-consuming, resource-intensive, and limited by API availability, especially during the early stages of drug development. Novel computational chemistry methods may assist in screening for API chemical stability prior to synthesis and augment contemporary API stress testing studies, with the potential to significantly accelerate drug development and reduce costs. In this work, we leverage quantum chemical calculations and automated reaction mechanism generation to provide new insights into API degradation studies. In the continuation of part one in this series of studies [Grinberg Dana et al., Mol. Pharm. 2021 18 (8), 3037−3049], we have generated the first ab initio predictive chemical kinetic model of free-radical oxidative degradation for API stress testing. We focused on imipramine oxidation in an azobis(isobutyronitrile) (AIBN)/H 2 O/CH 3 OH solution and compared the model's predictions with concurrent experimental observations. We analytically determined iminodibenzyl and desimipramine as imipramine's two major degradation products under industry-standard AIBN stress testing conditions, and our ab initio kinetic model successfully identified both of them in its prediction for the top three degradation products. This work shows the potential and utility of predictive chemical kinetic modeling and quantum chemical computations to elucidate API chemical stability issues. Further, we envision an automated digital workflow that integrates first-principle models with data-driven methods that, when actively and iteratively combined with high-throughput experiments, can substantially accelerate and transform future API chemical stability studies.

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