The Radiological Medicine Webzine interviewed Dr. Howard Lee, who shared his perspective on the new trend in clinical trials, reflected by the active employment of innovative technologies to survive stricter regulations and scientific requirements. The full interview can be found here and the school website has also highlighted it. 

Dr. Yuchae Jung wrote an article in BRIC View on Nov 20 2017 about AI techonology for the improvement of clinical trial process. In this article, Dr. Jung introduced several examples of global pharmaceutical companies that have successfully applied AI technology to drug development and clinical studies. She also added that AI technology can be used in various fields of drug development such as simulation of drug-drug interaction, drug screening, patient recruitment, and data collection from biosensors. Dr. Jung concluded the article by emphasizing the potential of AI technology in streamlining drug development processes. Dr. Jung's article can be downloaded here.

Hyewon Hwang, a 2017 summer intern of the Graduate School of Convergence Science and Technology, shared her internship experience at CCADD in an interview with GSCST Blog. During her internship, Hyewon was involved in a project where machine learning was used to solve real world problems in drug development, particularly at the junction of medicine and pharmaceutical science. She was impressed how diverse and share-minded the people at CCADD were. "It was truly what convergence should be all about", Hyewon added, "And, the internship program at CCADD was very well planned and thoughtfully organized such that I could learn and get exposed to the state-of-the-art application of deep learning to practical issues and problems." Hyewon also emphasized that she would recommend the internship program to anyone who would want to learn what life looks like at a graduate school. Hyewon's full interview can be watched here. 

Dr. Yuchae Jung introduced the concept of P-MATCH or Precision Machine Learning AssisTed Clinical Trial Eligibility Assessment using Hospital Records at the 5^th Joint Conference on Medical Device between Seoul National University Colleges of Medicine and Engineering and Seoul National University Hospital on November 3, 2017. The title of her talk was 'Application of Artificial Intelligence Technology for Efficient Clinical Trials'. Dr. Jung underlined why artificial intelligence, mainly deep machine learning, can and should be adopted to bring more efficiency to clinical trials, particularly for precise patient enrollment, which allows for patients who are likely to respond to a treatment under testing to have a bigger chance of enrollment. This will also make clinical trials more productive and error-free, Dr. Jung added, because all of the eligibility assessment procedures are algorithm-based using the electronic medical record (EMR). 

Dr. Jung's talk was well received, and there were a couple of questions as to what could make P-MATCH different from other approaches such as the IBM Watson for Oncology. Dr. Jung replied that the biggest difference is P-MATCH's natural language processing capability of more than one language (i.e., Korean and English), which often are used in EMR in a haphazard and inconsistent manner. 

For anyone who wants to learn more about Dr. Jung's presentation, please contact her. 

The Convergence Story, a periodical news letter published by the Graduate School of Convergence and Science Technology (GCST) at Seoul National University, interviewed Dr. Yuchae Jung on Sep 21 2017 about her past research experience and accomplishments, new research interests, and future plans. In the interview, Dr. Jung emphasized the application of artificial intelligence technology to streamline clinical drug development, particularly for efficient patient enrollment using machine learning algorithms based on the electronic medical record (EMR). More details about Dr. Jung's interview can be found at News letter.