Prof. Howard Lee gave a talk at the 17th JSCPT-KSCPT Joint Symposium, Kobe, Japan, on December 15, 2023. In his presentation entitled 'Real-World Data Analysis as a Clinical Pharmacologist: Experience and Some Thoughts', Prof. Lee. introduce the audience to the RWD research works CCADD has performed for the past 3 or so years, all of which have been published in reputable journals or under review shown below. Prof. Lee stressed, "With RWD landscape fast growing, clinical pharmacologists should leverage the potentials of RWD/RWE in drug development by furthering its scientific innovation!" 

Prof. Lee's speech was well received by the audience followed by a welcome reception by JSCPT colleagues, whom he and other delegates have not seen in person for the past three years because of the COVID-19 pandemic. The night was full of talking, drinking, and singing! Both teams promised to meet again next year in Jeju, Korea, for the Spring Conference of 2024 KSCPT. 

CCADD attended the 2023 Fall Conference of the Korean Society of Medical Informatics (KoSMI) held at HIP(Healthcare Innovation Park) of Seoul National University Bundang Hospital, South Korea. The conference spanned three days from November 29th to December 1^st, both online and offline. Aligned with the theme "Beyond Data: Actionable Health AI", the conference featured 27 symposiums covering various topics, from artificial intelligence in the healthcare to standardization of medical data and digital health.

The first day was conducted online. Particularly, ”Symposium 6: Development of Predictive Models for Cardiovascular Diseases Using Medical Big Data” was noteworthy, where Prof. Howard Lee served as the session chair and speaker, attracting significant attention from the audience with the presentation on ”Improving the Performance of Machine Learning Models for Predicting Acute Coronary Syndrome in Type 2 Diabetes Patients through Substitution of Propensity Scores for Binary Variables”. Also, throughout the conference, the poster presentation was led by David Seung U Lee.

On the second day, each symposium delved into topics of medical data and artificial intelligence applications to the healthcare domain. Themes included "Strategies for the Activation and Commercialization of AI-Based Drug Development" and "Smart Curation of Medical Data: Approaches for Preparing for the Utilization of Medical AI." This encompassed insights into the industry's latest strategies for drug target exploration. In Symposium 9, Dr. Siun Kim delivered a presentation on ”Addressing the challenges of data scarcity and bias of AI-based drug development”. The discourse extensively covered specific manifestations of data scarcity and proposed strategies for mitigation within drug development.

During the final day, the symposiums provided an opportunity to approach the trends in the utilization and data processing methods of developing LLM. Participants delved into the practical approaches for utilizing Real-World Data (RWD) in regulatory decision-making, replicating Randomized Controlled Trials (RCT), and employing common data models. CCADD members exchanged ideas with fellow researchers studying similar research topics, offering a valuable opportunity to comprehend ongoing research trends. It was an insightful symposium for healthcare information researchers to share and discuss the latest trends in research.

Prof. Howard Lee shared his past experiences and future perspectives on the 14C-based microtracing and macrodosing studies in humans in South Korea as an invited speaker to the 9th East Asia Accelerator Mass Spectrometry Symposium (EAAMS-9), held at KIST, Seoul, South Korea, on November 22-24, 2023. 

Prof. Lee has introduced the concept and utilizes of the 14C-based microtracing and macrodosing study for new drug development since 2024. As of today, Prof. Lee has completed a total of six microtracing/microdosing studies with one being the IND-opening study for the US FDA. In his talk, Prof. Lee shared his experiences in starting a 14C-labelled human study using the microdosing technology in Korea. Additionally, Prof. Lee gave hist perspective as to how this technology can be further utilized to increase the efficiency of clinical drug development.

Prof. Howard Lee gave a talk at an invited symposium in association with the Annual Conference of the Korean Society of Medical Informatics (KoSMI), held both online and offline on November 29, 2023. The title of his presentation was ‘Performance Increase of the Machine Learning Model to Predict Acute Coronary Syndrome in Patients with Type 2 Diabetes Mellitus by Replacing Binary Variables with Propesnsity Score’. This presentation was a culmination of a research project with the same title supported by the Seokcheon Foundation, 2023, where the current and former CCADD graduate students, namely David Seung U Lee, Jung-Hyun Won, and YeSol Hong collectively contributed by proposing a new novel way to address the falseness of binary feature in the electronic medical records. Prof. Lee's speech was well received by the audience evidenced by 6 follow-up questions! The more detailed methodological aspect of Prof. Lee' talk was presented in an accepted poster led by David Seung U Lee.  

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.

Prof. Howard Lee emphasized the willingness to pay for innovation from the whole societal perspective for South Korea. In a forum organized by Hankyung TV to commemorate the 2023 Korean Biopharmaceutical Award, Prof. Lee discussed what South Korea has to equip itself with to become one of the countries that can not only develop, but market innovative new drugs on a global scale. He listed the following conditions: nationwide control center, training and education, megafunds, advanced drug regulatory science, and willingness to pay for innovation as a society. The following YouTube clip captures the 5th condition.

"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. 

Prof. Lee stressed the co-vaccination with both COVID19 and Flu since we are entering into a season where flu can become epidemic while the antibody level against COVID19 might not be sufficiently high enough for protecting us from becoming seriously ill once infected. This statement was made in an interview with Arirang TV on October 6, 2023. Prof. Lee continued saying "the pandemic is over, but we are still living with the virus", which leads us to getting some protection against a new sub-variant of COVID19, which is XBB1.5. The two mRNA vaccines by Pfizer or Moderna, respectively, got cleared by the regulatory agencies, Prof. Lee added. A full interview can be watched at the following YouTube link.