Fighting Disease with Artificial Intelligence

Rui Yin (Ph.D. ’24, biological sciences) harnesses the power of AI to take on the challenges of drug discovery at Absci.

Rui Yin (Ph.D. ’24, biological sciences) is on a mission to fight human disease. In her research at Absci, a next-generation drug development company, the data-processing power of artificial intelligence (AI) is her most valuable tool.

“The ability of AI to see massive amounts of data and detect the underlying pattern of whatever problem that you are trying to solve, that really speaks to me,” Yin explained. “It’s almost like you have a fishing rod and a hook, and it’s not just a single hook, it’s this massive next-generation fishing system that has the potential to work so much more efficiently and unlock the cures for previously incurable diseases.”

In her work in antibody design and engineering, Yin aims to develop better biologics against undruggables—proteins that play a critical role in disease processes but are challenging to target with conventional drugs. By rapidly churning through massive amounts of data, AI helps Yin predict and design the complex antibody interactions that can lead to a treatment.

“Antibodies are little proteins, and if you unfold them, they’re like little strings of beads of amino acids. The possibilities to mix and match the beads are enormous,” she explained. “To test even a small fraction of the possibilities in a lab would be extremely costly and take months to complete, but AI can quickly evaluate the real-world possibilities, tease out underlying patterns, and help design new antibodies that are specific to your target and could ultimately be turned into a drug.”       

For Yin, who has contributed to antibody research for diseases ranging from cancer to coronavirus and hepatitis C, working with AI on the cutting edge of medical science is genuinely inspiring.

“I definitely have a lot of those wow moments, seeing what AI is capable of achieving,” she said. “I firmly believe that we are on the track of deepening our understanding of the immunology of protein-protein interaction, protein design and antibody engineering with tools that weren't even an option 10 or even five years ago.”

Growing up with medicine

Yin grew up with a father who was a doctor and a mother who was a nurse. She was reading medical books before she even reached high school.

“My parents’ work was a big influence on me for sure,” Yin recalled. “I remember piles of medical books—more than I could even carry. These were the books my parents read for their field of study, but I would just randomly open them and read them myself.”

Yin attended college at William & Mary in Virginia, where her biology classes introduced her to protein engineering and fueled her interest in the complex challenges of immunology. Then in 2019, seeing medical research in her future, Yin was accepted into the University of Maryland’s biological sciences Ph.D. program. 

“I wanted to find the right field of science where I could continue pursuing my passion for protein engineering and also be able to leverage the power of AI, even though it wasn’t something I was really familiar with yet,” Yin explained. “Although everybody's talking about AI now, it wasn't like that back then. I did know that I wanted to explore machine learning because I realized I wanted to achieve a widespread impact.”

In her Ph.D. research, Yin worked with Associate Professor Brian Pierce in the Department of Cell Biology and Molecular Genetics and the Institute for Bioscience and Biotechnology Research, developing and applying computer algorithms to better understand how the body’s immune system recognizes and fights pathogens and disease.

“It was in Brian's lab that I got the training I needed in order to succeed in this field,” Yin said. “When I first joined his lab, I knew virtually nothing about programming, and he was able to help me expand my knowledge and master state-of-the-art techniques. His lab is world-class, and being able to do research there gave me a front-row seat to observe what's happening in this field. I was very fortunate to be part of that.”

From the lab to the real world                                                         

In Pierce’s lab, Yin got her first exposure to deep learning in structural biology, working with programs like AlphaFold, the breakthrough AI system developed by Google DeepMind that predicts the 3D structure of proteins based on their amino acid sequence. Through her research, Yin developed and applied computational tools, including deep learning methods, to predict and model immune recognition, specifically studying the structures of antibodies and T-cell receptors interacting with their molecular targets. 

“These interactions underlie the body’s immune response against pathogens—antibody and T-cell receptors are proteins that the human body is capable of making that are really important for discovering and combating foreign invaders and also invaders from inside the body,” Yin explained. “My work provides tools to understand them and help researchers tap into the immune system’s power to combat diseases.”

For Yin, it was especially exciting to take her research from the lab to real-world applications.

“In our research, we found ways to improve antibody-antigen modeling success and were able to collaborate with amazing researchers within and outside the department to test our model in real life,” Yin said. “We were able to predict antibody-antigen interaction for COVID-19 and hepatitis C, which was super exciting.”

Yin’s graduate research and a fellowship from the National Cancer Institute advanced her progress toward her ultimate goal: making an impact in medicine.

“I've always wanted to be a useful person to society, and one way I see that I'm able to do that is to help advance our understanding of a particular protein or disease on the basic research level,” she explained. “I try to apply what I've learned and translate that into drugs that can help save human lives.”

Pierce sees tremendous potential for Yin’s work in the future.

“In this exciting time for the field, talented scientists like Rui are poised to do amazing things that leverage AI to combat disease and improve human health,” he noted. “Rui did very impressive and impactful work while in the lab, and I’m excited to now see her on the front lines using AI to develop new and important antibody therapeutics.”

As Yin works to develop the tools and the platform to use AI to design antibodies that can cure previously undruggable diseases, she is living out Absci’s company motto every day: ‘Achieving the Impossible.’

“I feel a calling to what I'm doing right now, and every day at work that gets reinforced,” Yin reflected. “I’m not the kind of person who exaggerates or oversells things, but I have to say I’m super excited about this research I’m doing, and what I can accomplish in this field in the future.”