Combining AI and Quantum Mechanics to Improve Drug and Vaccine Discovery

by Andrii Buvailo, PhD          Interview | Sponsored by PharmCADD

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Topics: AI & Digital   
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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.

 

Andrii: Can you briefly introduce yourself and how you became a part of PharmCADD’s story? A couple of words about the company’s services and your pipeline of products? 

 

Sangwook: In addition to my CEO/CTO position at PharmCADD, I am teaching physics at Pukyong National University in South Korea. Although I earned my bachelor’s degree in biochemistry, I realized that my academic interest was in biological physics as well as quantum physics. I followed my interest at the graduate schools and earned my Ph.D. in condensed matter physics at Iowa State University. I learned various computational chemistry principles and machine learning (ML) approaches during my postdoctoral training at the University of North Carolina at Chapel Hill. When I became a faculty member in 2014, the application of computational approaches including the use of AI/ML algorithms in drug discovery was still at the very early stage.  Mr. Taehyung Kwon, co-CEO of PharmCADD, quickly realized the huge potential of my research achievements when he visited my research lab, and encouraged me to build a biotech company together. Mr. Kwon and I made a business plan together in late 2018 and registered the company’s name in March 2019. That’s the history of PharmCADD. 

Our business model does not include “fee for service” at the moment, we would rather perform collaborative R&D with partners for an upfront fee (or, technology access fee), milestone-based payment, and royalty payment. We would also want to provide pre-clinically ready small molecule compounds for license-out deals. Currently, we are developing several internal and collaborative pipelines including anticancer drugs (Figure 1). We have also licensed-out thermostable and translationally efficient mRNA sequences of SARS-CoV-2 spike protein to a Korean biotech company, EyeGene. This pipeline is the first mRNA vaccine for COVID-19 in Korea which is in phase 1/2a clinical trial.     


 

Andrii: So, the company is developing both therapeutics and vaccines -- those are quite different things. How do you manage to run programs in those different areas simultaneously? What resources, including funding and team, do you have for such diverse scope of R&D efforts? 

 

As you mentioned, development strategies for small molecule therapeutics and for vaccines are quite different. I haven’t dreamed to develop both modalities when I formed the R&D team. As you might expect, I built R&D team focusing on small molecule therapeutics at first. However, COVID-19 came to us unexpectedly and the need for therapeutics became an imminent and urgent issue. Fortunately, I had research experience in nucleic acid 3D structure, and some of my R&D team members were trained in RNA sequence optimization research at MIT. In collaboration with EyeGene, which has ongoing vaccine programs with a promising liposome delivery technology, I could jump into the mRNA vaccine development program with strong confidence and enthusiasm. We anticipate that this vaccine program would enter into phase 3 in clinical trials in the second half of 2022. The motivation that I would run both small molecule therapeutics and vaccine programs come from the diverse research background and the high quality of my R&D team. PharmCADD has over 50 scientists and engineers in the R&D team, and among them, 35 scientists have Ph.D. degrees in the field of computational chemistry, physics, biology, and Artificial Intelligence. That is why we could carry diverse R&D programs like the kinase inhibitor, PROTAC, GPCR antagonist, drug delivery system (DDS), RNA-based vaccine, and RNA structure-targeting drugs. 

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Topics: AI & Digital   

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