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The Challenging Road to Developing an Integrated Platform for Drug Discovery and Precision Medicine Using the Power of Pharmacometrics

We have often seen Dr. Hwi-yeol (Thomas) Yun, Associate Professor/Adjunct Professor at the College of Pharmacy and Bio-AI Convergence Research Center of Chungnam National University, listed as a guest presenter at key Pharmacometrics conferences across the Asia-Pacific region, as well as at local Korean events. In 2020, he also presented to a large audience at Certara’s User Group Meeting for Korea. Now, we are happy to share with you with a deep dive into his career and achievements.

Can you tell us about your latest pharmacometrics project and publication?

Since I began working for the university, our research interests have covered a wide scope, ranging from the methodology to the applications of pharmacometrics (PMX). Recent projects related to applications of PMX have tended to focus on mechanistic modeling of systemic and lymphatic circulation as emerging trends in biologics drug development. As not much is known about PK/PD’s contribution to lymphatic circulation, deeper exploration in this area is considered one of the key challenges for PMX in the future.
One of the most interesting papers on this methodology published recently was the validation of the Michaelis-Menten (MM) equation improvement, which is widely used to predict hepatic clearance in the field of in-vitro/in-vivo extrapolation (IVIVE) (Ref.: Clin Transl Sci (2020) 13, 1199-1207, DOI: 10.1111/cts.12804). In writing this paper, we collaborated with drug metabolism and mathematics experts. During this process, pharmacometricians with an understanding of both these fields played a key role in explaining them. This experience left me with the impression that another possible role of pharmacometricians could involve consolidating our knowledge of different fields. In addition, the other papers we are currently working on focuses on the application of machine learning (ML) method to advance PMX. ML has been widely applied in the field of PMX in the past. As ML algorithms such as the neural network method and the transformer method have developed so rapidly, I felt that studying the application of this technology to PMX would be worthwhile. This research concluded that PMX combined with the above ML algorithm can be useful for showing high predictive performance using little information. The results of this have been very interesting and have given me confidence that PMX enhancement through ML could be a promising method.

How is your research project supported by Certara software and technology?

As the gold standard of pharmacometrics, Certara software and technology supports our research in various way, particularly when we are developing complex mechanism-based PK/PD models. The user-friendly Certara software interface has the power to maximize the capabilities of pharmacometricians. In addition, the high-quality plots reduces our workload when compiling results. This allows us to focus on working with other scientists to reach our goals. Finally, I want to emphasize the usefulness of Certara University, which provides many valuable PMX lectures for various levels of knowledge in the form of online courses. Whether at entry or expert levels, those interested can increase their knowledge
and become motivated to learn about science with Certara University. I strongly encourage you to take one of these courses, and I am sure you will understand why after you have completed it.

Do you have a future goal in mind regarding pharmacometrics/biosimulation technology?

The ultimate goal for our team regarding PMX is to create a method and platform for the integration of multiscale systems. Similar to superstring theory in physics, the attempt to cut through the hierarchy from genes to humans will play a very important part in improving the success rate of new drugs in development and the performance of precision medicine. Although there are many challenges left to face, various methods such as allometric scaling, quantitative systems pharmacology (QSP), and machine learning applications are being utilized with the aim of achieving this goal and showing promising results. Considering the pace of technological development, a validated integrated platform with sufficient predictive power is expected to appear within our lifetime. Hopefully, people will be able to develop new drugs and administer precision medicine supported by this platform, with low costs and high efficiency.

For those currently trying to decide on a major/career, can you share your thoughts on the
benefits of studying Pharmacokinetics at university?

While there are many benefits of studying PK, the main one is that it can help you to integrate knowledge about new drug development and precision medicine. As you may know, because PK is a discipline that seeks to understand the behavior of drugs in the body, basic knowledge of chemistry and biology is required to understand it. As the importance of statistics, mathematics, and computer science increases, studying PK also involves integration of various disciplines. Through this process, students will naturally develop their ability to understand problems using integrated knowledge and develop evidence-based scientific decision-making processes. I think that is most important benefits from learning and studying PK.


About the Pharmacy/Bio-AI Convergence Research Center, Chungnam National University

Chugnam National University (CNU) in Daejoen, South Korea, is one of the country’s top universities. Since the CNU was founded in 1952, around 20,000 students have been taught and conducted research in its 16 colleges, composed of 89 departments. The Department of Pharmacy and the Bio-AI Convergence Research Center, both of which Dr. Hwi-yeol (Thomas) belongs to, are ranked highest at CNU, and compared to other universities throughout the country. Dr. Hwi-yeol (Thomas) Yun is responsible for running the pharmacotherapy laboratory of this institute, in which students and researchers conduct PMX
research with the consensus of ‘leading in life science with advanced computing’. The laboratory consists largely of people who are open about their research and ready to collaborate with anyone keen to find scientific evidence for drug discovery and precision medicine.

Dr. Hwi-yeol (Thomas) Yun adds: “Don’t hesitate to contact me if you want to collaborate on something. It doesn’t matter whether it’s big or small.”


About the Interviewee

Hwi-yeol (Thomas) Yun, Ph.D. is an Associate Professor at the College of Pharmacy at Chungnam National University in Korea. He is a specialist for PK/PD modeling and simulation based on pharmacometrics-related techniques, Hwi-yeol is also skilled
in-vivo/in-vitro PK/PD modeling techniques from preclinical to clinical development. Hwi-yeol majored in Clinical Pharmacy/Pharmacokinetics and earned his Ph.D. at Chungnam National University’s College of Pharmacy. After this, he worked in the Drug Metabolism & Pharmacokinetics Laboratory of JW Pharmaceutical, while also serving as a pharmacometrics advisor at the Clinical Pharmacy of Seoul National University. Before joining Chungnam National University as a professor, Hwi-yeol was a postdoctoral fellow of a pharmacometrics research group in the Department of Pharmaceutical Biosciences at Uppsala University in Sweden. He returned to Chungnam National University after
conducting research at the University of California, San Francisco (UCSF) as visiting scholar from Sep. 2020 to Aug. 2021.


About the author

By: Certara