期刊
MOLECULAR PHARMACEUTICS
卷 19, 期 5, 页码 1526-1539出版社
AMER CHEMICAL SOC
DOI: 10.1021/acs.molpharmaceut.2c00043
关键词
pharmaceutical stress testing; predictive drug degradation; AIBN-initiated autoxidation; chemical stability; ab initio kinetic modeling; imipramine
资金
- Pfizer Inc.
- National Science Foundation [479590]
- George J. Elbaum Scholarship in Engineering
- Zuckerman STEM Leadership Program
This paper highlights the potential of using computational chemistry methods to study API chemical stability and proposes the concept of an automated digital workflow. By leveraging quantum chemical calculations and automated reaction mechanism generation, a predictive chemical kinetic model of free-radical oxidative degradation for API stress testing is created and compared with experimental observations.
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 computationalchemistry methods may assist in screening for API chemical stability prior to synthesis and augment contemporary API stress testingstudies, with the potential to significantly accelerate drug development and reduce costs. In this work, we leverage quantum chemicalcalculations and automated reaction mechanism generation to provide new insights into API degradation studies. In the continuationof part one in this series of studies [Grinberg Dana et al.,Mol. Pharm.202118(8), 3037-3049], we have generated thefirstab initiopredictive chemical kinetic model of free-radical oxidative degradation for API stress testing. We focused on imipramine oxidation inan azobis(isobutyronitrile) (AIBN)/H2O/CH3OH solution and compared the model's predictions with concurrent experimentalobservations. We analytically determined iminodibenzyl and desimipramine as imipramine's two major degradation products underindustry-standard AIBN stress testing conditions, and ourab initiokinetic model successfully identified both of them in its predictionfor 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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