Unsymmetrical sulfamides are important as drugs and drug candidates. Conventional acidic synthetic approaches
from sulfuryl chloride usually require multiple steps and harsh reaction conditions, threfore, they are not applicable to the synthesis of unsymmetrical sulfamides containing acid-labile groups. Sequential introduction of different amines against sulfuryl chloride under basic conditions is an ideal approach, however, it suffers from side reactions such as symmetric sulfamide formation and base-mediated conversion of sulfamoyl chloride to sufonylimine and the following dimerization or polymerization. Here, we report the first rapid and mild (5.1 s, 20 ℃) one-flow synthesis of unsymmetrical sulfamides via sequential introduction of different amines against sulfuryl chloride. The reaction conditions producing ≥75% yield had been identified using a machine learning based on Bayesian optimization (BO). It was demonstrated that BO produced the desired reaction parameters with a small number of experiments (< 100) and yields Gaussian process (GP) models describing the relationships between combinations of reaction parameters and reaction outcomes. These models could be used for gaining valuable insights into synthetic reactions. GP models produced by BO identified the critical role of viscosity as determined by temperature and concentration. We synthesized 15 unsymmetrical sulfamides including acid-labile groups in good yields.

Development of a One-Flow Synthetic Approach to the Unsymmetrical Sulfamides Utilizing Bayesian Optimization

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