Generating flavors using Scientific Machine Learning
Luana P. Queiroz, Carine Menezes Rebello, Érbet Almeida Costa, Vinícius V. Santana, Bruno C. L. Rodrigues, Alírio Egídio Rodrigues, Ana Mafalda Ribeiro, Idelfonso B. R. Nogueira · Research Square · 2022
Abstract The flavor is an essential component in developing numerous products in the market. The increasing consumption of processed and fast food and healthy packages has upraised the investment in new flavoring agents and, consequently, molecules with flavoring properties. In this context, this work brings a Scientific Machine Learning approach to address this product engineering need. Scientific Machine Learning in computational chemistry has opened paths in predicting a compound's properties without requiring synthesis. This work proposes a novel framework of deep generative models within this context to design new flavor molecules.