Combining AI and Quantum Mechanics to Improve Drug and Vaccine Discovery

The application of Artificial Intelligence (AI) to accelerate and improve drug discovery has been a growing trend for several years in a row, with the increasing number of AI-inspired drug candidates entering clinical trials. While AI proved to be a powerful tool for modeling biological systems and helping generate optimal leads, it is important to remember that deep learning (DL) -- the heart of the modern “AI revolution” -- is only as good as the underlying data used to train models. Since the majority of AI-driven companies are “playing” with classical Newtonian mechanics to describe the motions of atoms and molecules, sometimes they can run into limitations of “classical physics” as a tool to describe biological systems, hence, lower ability to grasp the intricacies of biology. 

A small number of companies are combining the latest advances in artificial intelligence research with the application of quantum mechanics (QM) methods to more accurately describe the behavior of the electrons in atoms and molecules, thereby getting better prediction results for, let’s say, ligand-target binding scenarios. 

One such company, a South Korean biotech PharmCADD, caught my attention recently because of two reasons. One reason was that the company offered a platform-based AI-driven system for drug discovery, involving quantum physics modules -- a promising combination. Another reason -- the company focused on a surprisingly wide diversity of various drug modalities and target types, and it even had a clinical-stage mRNA-vaccine candidate in its pipeline -- in collaboration with an external partner.

Below is my interview with Dr. Sangwook Wu, CEO/CTO at PharmCADD, where he explains how their technology operates, what the role of AI and quantum physics in drug discovery is, and how drug makers can partner with such AI-platform companies as PharmCADD to leverage technology and enrich their pipelines with promising assets.

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Topics: AI & Digital