Prof. Howard Lee spoke at a conference held by The Korean Society of Food, Drug and Cosmetics Regulatory Sciences, December 13, 2024, in the Hoam Faculty Club, Seoul National University. Prof. Lee discussed the current status and future perspectives as to the application of artificial intelligence technologies to clinical drug development. A newspaper article focused on the point that Prof. Lee emphasized at the Q&A session, where Prof. Lee stressed the establishment of the standards in order for AI to be more broadly accepted into the real-world practices of drug development, particularly for the clinical stage including post-marketing approval.

This summer, CCADD welcomes three interns-Kim Chanmin, Choi Yunjin, and Yoo Kyungwan -for the 2024 Summer Internship Program.

Kyungwan Yoo, a student at Kyung Hee University, earned his Bachelor’s degree in genetic engineering. He worked as an undergraduate researcher at the Kyung Hee University Regenerative Medicine Institute, focusing on creating cell-targeting treatments. Currently, he is interested in integrating biological science with artificial intelligence (AI) technology and applying it to drug development. Kyungwan applied for the 2024 CCADD Summer Internship Program to expand his knowledge of drug development in general, be it clinical trials, and/or utilizing medical big data. He also intends to gain practical experiences in applying programming languages to these domains.

Yunjin Choi has graduated from Stony Brook University with a Bachelor’s degree in mathematics. After graduating, Yunjin worked as a statistical analyst at the Biomedical Research Institute, Korea University Guro Hospital. She has mainly conducted retrospective studies on nephrology and neurology. For example, she published a paper entitled "Fasting glucose variability and risk of dementia in Parkinson's disease: a 9-year longitudinal follow-up study of a nationwide cohort", which examined the impact of fasting glucose variability on the risk of developing dementia in Parkinson's disease patients over a nine-year period. The study found that greater variability in fasting glucose levels was associated with a higher risk of dementia, further suggesting that stabilizing glucose levels might be beneficial for cognitive health in these patients. Besides being the first author of the study, she was also responsible for data analysis and interpretation, ensuring the accuracy and reliability of the study results. She also has the opportunity to learn how to draft and revise the manu and enhance its scientific merit. During this time, Yunjin developed an interest in Real-World Data (RWD), such as electronic medical records (EMR). She intends to pursue her interest while at CCADD.

Chanmin Kim is a Biological Engineering major at Kangwon National University. She became interested in developing new drugs while learning drug delivery systems. She also completed GMP training. After receiving the Excellence Award for designing smart healthcare products at Gachon University's DNA (Data, Network, AI) School Camp , she became interested in improving the efficiency of developing new drugs by applying data science and AI. Her goal is to become a researcher in the development of new drugs using AI. Through her 2024 CCADD summer internship program, she will pursue this goal.

We hope that during their summer internship, they will gain confidence in their field of study, learn how to study independently and explore new knowledge, and devote all their passion to gaining a deep understanding of drug development and regulatory science over the course of these two months.

CCADD members attended the Annual Conference of the Korean Society for Clinical Pharmacology and Therapeutics (KSCPT), taking place at Sono Belle, Gyeongju, from November 16th to 17th. In this conference, approximately 300 participants shared their insights and findings in the translational pharmacometrics and new drug development realms. 

Representing CCADD, graduate students Tae Kyu and Yoona have delivered oral presentations on the latest advancements in clinical pharmacology and related scientific disciplines at the Conference.

Tae Kyu's oral presentation, centered around the research entitled "Comparison of Machine Learning and Population Pharmacokinetic Models for Predicting Antiepileptic Drug Concentrations Based on Therapeutic Drug Monitoring Records," acquired substantial attention, particularly from pharmacometricians. During the presentation and subsequent discussions, he shared insights on how the application of machine learning to clinical pharmacology holds the potential to revolutionize drug development, dosage optimization, and personalized medicine. 

Yoona also presented her research topic, entitled "Country Contribution of Investigators to Pivotal Clinical Trials and THeir Primary Publications of New Drugs Approved by the US Food and Drug Administration," emphasizing the need for Korean researchers to take an active leadership role in key clinical trials to secure opportunities to contribute as authors to primary publications. The audience also agreed with her suggestions and provided constructive feedback, e.g., why it is not easy to be the author in the primary publications. After her presentation, she commented that it was a valuable opportunity to gauge the interest of clinical pharmacologists in that subject matter. 

In this conference, Tae Kyu and Yoona were bestowed with the esteemed "Best Presentation Award," marking a significant achievement and recognition for their outstanding presentation skills. Out of around 50 accepted abstracts, only the 7 presentations were deemed worthy of the best presentation title. Tae Kyu and Yoona's work was further celebrated with a cash prize of 100,000 KRW.

After all the programmed sessions were over, attendants eagerly awaited the prize draw. In a moment of drawing for the first gift, Howard emerged as the fortunate recipient. With his jaws on the floor, Howard made his way to claim his prize, a Bluetooth Sony Headphone. The annual conference held by KSCPT was a stage to celebrate the lab's commitment to excellence and an opportunity to showcase our gratitute for the fortune we have experienced.

"Artificial Intelligence (AI) has a bright future in the area of drug discovery and development", Prof. Howard Lee agreed. But, he went on saying, "The focus has been drug discovery, particularly de novo search of new 'drug-like' molecules, which came up with a mix of some successes and mostly failures." To Prof. Lee, there is a more important area where AI applications have not been tried much, and that is clinical development, more expensive, lengthy, and riskier. These statements were made at a K-Healthcare Business Forum, co-sponsored by Young Doctors, KBR, and KHIDI, on October 13, 2023.

In a speech entitled "AI-based drug development: Hype or Reality?", Prof. Lee explained why the application of AI technologies has been mostly limited to early stage or drug discovery, and how this can be expanded to the later phase of drug development such as preclinical toxicity prediction and more robust and efficient design and conduct of clinical trials. The details of Prof. Lee's talk can be found in this news paper article. 

Jung-Hyun Won was invited to the KOREA AI SUMMIT 2022 (“AI for Good”), where she presented the collaboration research project between CCADD (Siun Kim, Jung-Hyun Won, David Seung U Lee, and Prof. Howard) and Microsoft Research Asia (MSRA) entitled “Revisiting and Reformulating Machine Learning-based Drug Repositioning”, orally and as a poster. The Korea AI Summit 2022, organized by AI Innovation Hub, Microsoft Research, IITP, and Korea University AI Research Institute, aimed to provide a platform for academic leaders from the prominent universities and institutes to share and explore the latest developments and technological trends in AI research.

Jung-Hyun Won stated that the team (i.e., CCADD and MSRA) has pointed out problems in the current task formulation of machine learning-based drug repositioning studies. According to Jung-Hyun Won, the team has found the spurious correlation between data collection pattern of drug characteristics and approved indications of drug. They also found that train-test split based on random sampling led to the overestimation of the performances of existing DR models. Jung-Hyun Won stressed that the team is currently reformulating drug repositioning problem as predicting investigational disease and generating eligibility criteria of clinical trials for a drug-disease pair.

Technology showcase can be watched the following youtube thumbnail.