Dawn
Please introduce yourself.

Kyle (Dr. Kyoungyeul Lee)
Hello, my name is Kyle, and I am leading the AI team at 3billion. Nice to meet you.

Dr. Kyoungyeul Lee, reviewing

Dawn
You joined 3billion after completing your bachelor’s and doctoral degrees in bio and brain engineering at KAIST. I know that you had many concerns due to various personal circumstances when joining the company. Still, what motivated you to join 3billion?

Kyle
Hmm... At the time, it was difficult for me to choose whether to go abroad to study to deepen my studies or compromise with reality and get a job. I also had job interviews with many other companies besides 3billion. I have lived my life thinking that it is crucial to do something that I can continue to grow on my own. From that point of view, I felt that continuing the research I had been doing was not the best option for my personal growth. I decided to join 3billion because I was looking for a company where I could grow by doing various research in a slightly different field from my previous studies Oh, of course, thinking that the company had great leadership also influenced the decision. To be honest, I thought, 'If I go to this company, I won't have to go through all sorts of hardships on my own.'

Dawn
Okay, thank you for your honest answer. You mentioned earlier that you chose the company because ‘I wanted to do various research in a slightly different field than before.’ What is the difference between the research you are doing now at 3billion and the research in the degree program?

Kyle
I studied bio and brain engineering in my degree courses, and it is a study that combines biotechnology with computer science (computing science) and other fields. I have been interested in computer science and biotechnology since I was little, so I chose that major. I started with a computing-based structural biology study and then studied to understand protein interactions within the human body. However, I wondered if I could continue to grow in this field. Around this time, I was interested in and started to research artificial intelligence-based drug development.
Then, the ‘AlphaGo Shock’ started in GO, shoking the world and my mind. At the time, I was convinced that developing and researching drug generation models using deep learning would be very promising and become a reality in the future. Of course, after conducting drug generation model research (deep learning) myself for two years, I felt some limitations (the gap between generation models and evaluation models, etc.). I realized that it was not easy. As you know, the study I did in my degree program and the research I'm doing now at 3billion are similar in some ways and different in others. So, I said something like that.

Dawn
Okay, I understood it well. So, what kind of research are you currently conducting at 3billion?

Kyle
Surprisingly, the problems I struggled with for two years during my degree course were somewhat solved through a few theses when I joined 3billion. Since then, we have developed top-class AI drug development models in Korea and achieved remarkable results thanks to the commitment and talents of our AI team members. We are currently improving these models and preparing a thesis for publication.

Dawn
It's only been about two years since you joined the company, but you've made significant progress. You mentioned that you could get results so quickly because of the commitment and talent of your team members. What are the other strengths of 3billion?

Kyle
When developing new drugs using AI, one of the most important things is genomic data if we assume that the target is a patient with a rare disease. Of course, some genomic data is meaningless, such as genomic data containing only DNA sequences. The critical data is ‘patient-centered data’ that can interpret which genetic mutation becomes the etiology of which disease. The data we have is fit into that category. It contains information from variants and phenotypes to etiological diagnosis.

Dawn
Uh, wait a minute. Some parts are difficult to understand. Why are those types of data important?

Kyle
Let me be more specific. Unlike general diseases, the etiology of rare diseases is less influenced by environmental and acquired factors. It is easy to use genetic data in medicine development because ‘variants in the genome’ are the direct ‘causes’ of patient diseases. Therefore, 'patient-centered data' is vital in developing cures for rare diseases. For example, let's talk about the cures for rheumatoid arthritis. Rheumatoid arthritis is an autoimmune disorder. The immune system is weakened when a particular gene loses its function due to a mutation. Based on these findings, a drug for rheumatoid arthritis that targets the corresponding gene was developed. Of course, it is difficult to identify the function loss of each gene case by case. However, if you have an AI capable of big data analysis, it can be solved with a system.

Dawn
Yes, it is easy to understand with your explanation. You are certainly eloquent. Are there some areas that need to be improved for future research?

Kyle
The system or data is sufficient now. Generation and evaluation models to utilize these systems and data are also being developed smoothly. However, AI-driven drug generation and evaluation models are based on synthesis rules. It means that we are conducting simulations by imitating some of the structures of the whole, focusing on those that have been synthesized. That's why we need experts who can verify whether this synthetic process is possible or not. So, we are currently hiring pharmaceutical chemists.

Dawn
Many companies other than us use computing technology such as artificial intelligence (AI) to develop new drugs. I think you are also well aware of it. In that sense, please tell me about the unique strengths of this company to those who are thinking about applying for the pharmaceutical chemist position currently hiring at the company.

Dr. Kyoungyeul Lee and 3billion members having discussion looking at a monitor

Kyle
Indeed, it is an HR manager-like request.
First of all, I think that the performance of the drug generation and evaluation models created by our AI team is at the top level in Korea. All indicators, including simulation results, proved what I thought. This will also be confirmed in papers we will publish in the future. You can also feel the reward of contributing to society. This is because what we are doing can help patients with rare diseases who are in the blind spot of new drug development. There are approximately 7,000 rare diseases, and around 250 new rare diseases are discovered every year. However, only about 5% of these diseases have a cure. Therefore, our company's new drug development research can help the remaining 95% of patients who suffer from a lack of available cures.

Dawn
I have some additional questions so that I can promote the company. During the hiring process, I get a lot of questions from potential applicants that are AI engineers from various fields. The most frequently asked question was this one. “My current research field is NLP or Vision, far from Bio. Is it possible for me to work as an AI engineer at 3billion?” As an AI team lead, what do you think about this question?

Kyle
I want our team members to keep improving. The same goes for me. That's why we regularly run deep learning study groups within the team. We share the latest deep learning technologies and apply them to our actual work. We also operate an AI drug development study group. In this study, we listen to the lectures of the experts in the field together, share relevant information, and work hard to develop our skills together. I think deep learning is a field that requires continuous study.
In other words, if you conducted research in fields such as NLP and Vision, it is just what you did in the past. As an AI engineer, if you can find and read the papers on your own and implement them in coding, you deserve to work at 3billion regardless of what kind of research you did in the past.

Dawn
Thank you. I think many people who are hesitant to apply for a position at the company will actively apply for the job because of this interview.

Kyle
That would be nice. I think recruiting good talent is the most important thing for our research. Also, it was an excellent opportunity to summarize my research history and company life through the interview. Thank you.