Research summary
The pace of new drug discovery is in sharp decline because the number of easily identifiable new drug classes is dwindling. For many types of treatments, researchers urgently need to find innovative ways to design new compounds. In recent years, researchers have increasingly applied generative deep learning-which uses artificial intelligence (AI) to interpret data-to drug design. But the process still suffers from problems with interpretability and a lack of scalability.
Dr. Rachael Mansbach, Canada Research Chair in Computational Physics/Biophysics, is working to fill this gap. Mansbach and her research team are using physical principles to direct cutting-edge AI techniques to understand biophysical processes. They are also using them to identify unique design rules for molecules and short proteins for drug uses like combating antimicrobial resistance and reducing chronic pain.