RESUMO
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)/H2O/CH3OH 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.
Assuntos
Imipramina , Modelos Químicos , Estabilidade de Medicamentos , Radicais Livres , Cinética , OxirreduçãoRESUMO
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.
Assuntos
Metanol/química , Modelos Químicos , Nitrilas/química , Água/química , Álcoois/química , Simulação por Computador , Radicais Livres/química , Concentração de Íons de Hidrogênio , Cinética , Oxirredução , Espécies Reativas de Oxigênio/química , Software , TemperaturaRESUMO
We herein report the development of a conformationally defined, electron-rich, C2 -symmetric, P-chiral bisphosphorus ligand, ArcPhos, by taking advantage of stereoelectronic effects in ligand design. With the Rh-ArcPhos catalyst, excellent enantioselectivities and unprecedentedly high turnovers (TON up to 10 000) were achieved in the asymmetric hydrogenation of aliphatic carbocyclic and heterocyclic tetrasubstituted enamides, to generate a series of chiral cis-2-alkyl-substituted carbocyclic and heterocyclic amine derivatives in excellent enantiomeric ratios. This method also enabled an efficient and practical synthesis of the Janus kinase inhibitor (R)-tofacitinib.
Assuntos
Piperidinas/síntese química , Pirimidinas/síntese química , Pirróis/síntese química , Ródio/química , Catálise , Hidrogenação , Ligantes , EstereoisomerismoRESUMO
High-throughput experimentation (HTE) has the potential to improve our understanding of organic chemistry by systematically interrogating reactivity across diverse chemical spaces. Notable bottlenecks include few publicly available large-scale datasets and the need for facile interpretation of these data's hidden chemical insights. Here we report the development of a high-throughput experimentation analyser, a robust and statistically rigorous framework, which is applicable to any HTE dataset regardless of size, scope or target reaction outcome, which yields interpretable correlations between starting material(s), reagents and outcomes. We improve the HTE data landscape with the disclosure of 39,000+ previously proprietary HTE reactions that cover a breadth of chemistry, including cross-coupling reactions and chiral salt resolutions. The high-throughput experimentation analyser was validated on cross-coupling and hydrogenation datasets, showcasing the elucidation of statistically significant hidden relationships between reaction components and outcomes, as well as highlighting areas of dataset bias and the specific reaction spaces that necessitate further investigation.
RESUMO
A mild, high-yielding, and practical protocol for the direct amidation of alkyl cyanoacetates using DBU is presented. This method eliminates the need for activation of cyanoacetic acid and/or high temperatures. It has been applied to the large-scale synthesis of CP-690,550-10 (1), a compound under development for the treatment of autoimmune diseases.