Hired through the University of Florida’s Artificial Intelligence Initiative, Dr. Jon Kim joined the UF College of Veterinary Medicine faculty in May as an assistant professor in the college’s department of small animal clinical sciences.
Kim holds a D.V.M. and a Ph.D. in veterinary pathology from Konkuk University in South Korea, where he established a program in veterinary and comparative oncology research. He completed postdoctoral work at the University of Minnesota and Masonic Cancer Center, where he also established an independent comparative oncology research program. In his new role at UF, Kim will focus on developing novel diagnostic and clinical applications in the field of comparative oncology and translational medicine by utilizing AI and machine learning.
Q: Dr. Kim, welcome! You’ve been at UF now for a few months. Could you elaborate briefly about your background, particularly in establishing the programs you completed at Konkuk and also at Minnesota relating to comparative oncology research?
Absolutely! I earned my D.V.M. degree in South Korea with enthusiasm for helping sick animals. When I started my graduate program in veterinary pathology, I had a lot of diagnostic cases for tumors in dogs— particularly, for canine mammary tumors, which are the most common tumors in the world with the exception of the United States due to the prevalence of early neutering of female dogs in this country. With these numerous cases, I completed my graduate project to better understand tumor immunity and the molecular characteristics of canine mammary tumors from a comparative perspective relative to human breast cancers. That experience led me to join the University of Minnesota, where an animal cancer and comparative oncology research program was established between the veterinary clinical sciences department and the Masonic Cancer Center, as a post-doc.
Q: As a veterinarian with a Ph.D. in veterinary pathology, how did you become interested in comparative oncology and translational medicine? What drew you to this area of interest and why?
To be honest, I never thought about becoming a researcher when I started veterinary school. Being a veterinarian and working as a clinician to treat sick animals in veterinary clinics was always my dream. However, the longer I studied in vet school, the more I encountered challenges and frustrations that we were not able to do anything further to help animals and owners suffering from devasting diseases such as cancer.
I had a strong feeling that we needed to better understand the pathogenesis of diseases. That’s why I pursued my graduate program in veterinary pathology. As a participant in the animal tumor diagnostic center at Konkuk University during my graduate work, I saw a lot of animal cases with cancers. As a pathologist, in most cases, we are not able to distinguish between human and animal tissues without sample history and supporting information. If you look at tissue slides under the microscope, you will recognize just “purple and red colors”, also known as Hematoxylin & Eosin stain images, which are used as a gold standard diagnostic method. Although pathologists can determine whether what they see is cancer or not, they are unable to tell you or anyone which species it is.
Cancers naturally occur in dogs very frequently, just as they do in humans. I was very curious as to why we often see the kind of same disease between dogs and humans. That’s why and how I started my research in comparative oncology. We still don’t know exactly why cancer happens, when it starts, or how we can stop it, but I believe that our efforts in comparative oncology could change the world for both animals and humans.
Q: What are the problems you are trying to solve and how are you approaching these solutions using artificial intelligence?
One of our main goals in using AI technology is to discover new ways to use data to better understand how diseases develop and progress. There is a misconception that the machine’s capabilities will replace humans, but our approach is not to train machines to do the same tasks that humans can do. Advances in biotechnology over the past decades have led to vast stores of biological and medical data, which will continue to accumulate. But we need to use our human analytical and interpretive skills to determine what this big data means, exactly, and what it can do.
We as humans can use machines that help us speed up analysis of big data and in finding biological meanings. Machines can do simple math very quickly, but they don’t know what it means and why it is important, or how to interpret computations in a context of biology. Also, machines can do many things in different disciplines, but we have to know how to use them. In biomedical research, we have to address very specific questions that are scientifically and biologically reasonable, and we have expertise in doing that.
I would just re-emphasize that we use AI to find new things and meaningful clues that might have an impact on disease detection, treatment, and prevention. As a veterinarian, basic scientist, comparative oncologist and pathologist, I use my comprehensive professional background in designing studies to use AI appropriately and efficiently. By doing so, I am eager to revolutionize this field and help animals and humans in the real world.
Q: Obviously you saw the job posting for the Florida position and went for it. What was it about the job here at UF that appealed to you? How does what UF has to offer complement your background and areas of interest?
Comparative oncology is a growing area of scientific and clinical interest, in companion animals such as dogs and cats that develop cancers naturally. Given challenges with translating findings from laboratory animals such as mice and rats to humans, people are becoming more interested in studying naturally occurring cancers in companion animals.
The UF College of Veterinary Medicine has an outstanding small animal hospital, where the second largest number of animal patients and owners are visiting among veterinary teaching hospitals in the United States. This was a very positive and attractive point to me. Importantly, despite the growing interest in comparative oncology due to a large number of cancer cases, there are different types of challenges in doing actual research on animal cancers in this field.
I brought up some of these barriers when I had my interview with the search committee and collegial and departmental leadership, and they provided a clear vision and mission. They were strongly enthusiastic in their support of my work and comparative oncology research overall, which was astonishingly impressive and a great incentive to for me to move here. Finally, UF has established one of the most advanced supercomputers in the world, which researchers are able to access and use. Altogether, UF is a strong fit for me to be able to envision a bright future in my career.
Q: Your bio states that your primary research interest lies in defining the fundamental mechanisms of cancers, particularly brain tumors, soft tissue sarcomas, and bone tumors such as osteosarcomas, which occur naturally in companion dogs and children, and that your team is focused on revolutionizing comparative oncology research to improve human and animal health. Can you elaborate on why you felt UF was such a good fit for these interests?
I want to elaborate on the collaboration aspect. I love science and enjoy talking with other scientists from different disciplines. I have had multiple collaborations with others including basic scientists, engineers, veterinarians, and human clinicians. I believe that this is key for enriching research activities and communities in veterinary schools, and in turn it will revolutionize the comparative oncology field.
Q: You recently published a paper on “Machine learning application identifies novel gene signatures from transcriptomic data of spontaneous canine hemangiosarcoma.” Is this particular cancer one you have kind of made a focus on in your work? Are you working with AI to deal with other types of cancers as well?
Hemangiosarcoma is a very important disease in veterinary oncology, as so many lovely dogs are suffering from it. For my part, I am accelerating my research activities for hemangiosarcoma at UF. However, my work and interests are not limited to one disease. My goal is to expand and maximize our ability and technology to help other types of cancer patients as well.
Q: How is Gainesville so far? Are you settling in? What are you working on right now and what do you hope to accomplish in the short term and in the long term?
I love Gainesville! I enjoy the atmosphere of warmth and collegiality I have found here so far. Gainesville has a definite vibe of positive energy and people have been so kind and supportive. I feel a great growth potential not just in the city, but also in my own career. I am currently setting up my lab at UF, including training, development of safety and experimental protocols, equipment purchase, and importantly, hiring people.
In the short term, I will complete my projects with new colleagues working in my lab at UF. Specifically, I have two sponsored projects: one from the AKC Canine Health Foundation for canine hemangiosarcoma and one from Department of Defense cancer research program for human angiosarcoma. These simultaneous grants are great sources for my comparative oncology research. Completion of these projects and achievement of the milestones will help me achieve our long-term goal, which is to develop clinically-relevant applications for cancer patients using AI.
Q: Is there anything else you would like to add that we haven’t asked you about?
I think our conversations have covered most of the key things about me as a basic introduction, although not nearly everything about me! I am looking forward to talking more about our work in the near future. Thank you for taking your time to do this interview It was nice answering your questions and sharing my story!