Publications and Presentations

Imputation of sensory properties using deep learning – ACS Spring 22

Mar 21, 2022

Imputation of sensory properties using deep learning – ACS Spring 22

Mar 21, 2022

Presented by Dmitriy Chekmarev (IFF) and Samar Mahmoud (Optibrium), on 20 March 2022 at the ACS National Meeting and Exposition, USA

Presentation Overview

We demonstrate how Augmented Chemistry®, a unique deep learning method, can learn from higher throughput data together with limited panel data to provide high-quality imputations for sensory properties.
• Find novel active compounds with 3D virtual screening against known actives:
• Demonstrate the imputation of sparse physicochemical and sensory data
• Compare the results with conventional quantitative structure-activity relationship (QSAR) methods
• Present robust uncertainty estimates generated by the imputation model, highlighting the most accurate predictions to guide decision making
• Show that imputation more accurately predicts activity cliffs, where small changes in compound structure result in large changes in sensory properties.

 

You can download the presentation slides as a PDF