Dr Soko Setoguchi
Rutgers Robert Wood Johnson Medical School
Most recently, she has been focusing her efforts on pharmacoepidemiologic and health services/outcome research to understand and address health issues and interplay between medications and climate change, the single biggest health threat facing humanity by WHO.
Studying and practicing medicine and pharmacoepidemiology in both Japan and the USA, Dr Setoguchi is passionate about globalizing and ‘futurizing’ pharmacoepidemiology and health service/outcome research by actively teaching in and outside of the USA, training global scholars of diverse background, and collaborating with non-US institutions on NIH funded studies.
Pharmacoepidemiology for the future in Asia-Pacific and around the globe
Soko Setoguchi, MD, DrPH, Professor of Medicine and Epidemiology at Rutgers University and Chair of the ACPE International Steering Committee, will review the state of the art in pharmacoepidemiology including the advancement of RWE methods, use of RWE for regulatory decisions, and multi-database studies/collaborations and their implications in Asia. She will then discuss ‘pharmacoepidemiology for the future in Asia-Pacific and around the globe’. Dr. Setoguchi will share her global perspective as a pharmacoepidemiologist, applied methodologist, clinician and global citizen, focusing on the role of pharmacoepidemiology in advancing data science, addressing the climate crisis, and educating the public and future pharmacoepidemiologists.
Hot topic speaker
Dr Yingfen Hsia
Queen's University Belfast
Clinical application of applying machine leaning to determine empirical antibiotics treatment in bloodstream infections
The key to prescribing appropriate antibiotics in clinical practice relies on culture-based antibiogram results. However, it is usually time consuming and costly. Many resource-limited settings may not have laboratory facilities. Applying machine learning algorithms to datasets could assist the development of a clinical decision tool to improve empiric prescribing with widespread utility. This could have a profound effect on antibiotic prescribing and would be especially valuable to healthcare workers especially in low- and middle-income countries who do not have access to the facilities required for rapid antimicrobial sensitivity testing, thus improving the chances of correct and effective treatment worldwide.
Hot topic speaker
Prof Sun-Yuan Hsieh
National Cheng Kung University
Dr. Hsieh is an experienced editor with editorial services to a number of journals, including IEEE Transactions on Computers, IEEE Transactions on Reliability, IEEE ACCESS, Journal of Computer and System Science (Elsevier), Theoretical Computer Science (Elsevier), Discrete Applied Mathematics (Elsevier), Journal of Supercomputing (Springer), Editor-in-Chiefs of International Journal of Computer Mathematics (Taylor & Francis Group), Parallel Processing Letters (World Scientific), Discrete Mathematics, Algorithms and Applications (World Scientific), and Managing editor of Journal of Interconnection Networks (World Scientific).
Predicting colorectal cancer survival from whole slide images using deep Learning
Many methodologies for selecting histopathological images, such as sample image patches or segment histology from regions of interest (ROI) or whole-slide images (WSIs), have been utilized to develop survival models. It remains challenging to obtain clinically prognostic and explainable features from gigapixel WSIs with diverse histological appearances. Therefore, we propose a survival prediction approach based on histopathological and image segmentation features extracted from WSIs. The cancer genome atlas colon adenocarcinoma (TCGA-COAD) dataset was used in this investigation. DeepConvSurv extracts histopathological information from the image patches of nine different tissue types, including tumors, lymphocytes, stroma, and mucus. The tissue map of the WSIs was segmented using image processing techniques that involved localizing and quantifying the tissue region. We extracted 128 histopathological features from four histological types and five image segmentation features from WSIs to predict colorectal cancer survival. Our method performed better in six distinct survival models than the WSISA adaptively sampled patches using K-means from WSIs. Using a combination of deep-learning-based histopathological characteristics and image segmentation, we demonstrated a clinically relevant survival prediction model.
AsPEN symposium: Rising Investigator Asian-Pacific Regions
The AsPEN symposium will highlight the missions, achievements and strategies of the AsPEN and will also showcase presentations from three groups of young researchers who have collaborated on cross-country projects in Pharmacoepidemiology. These young researchers are competing for a new award, the AsPEN Rising Investigator, Asian-Pacific Regions which will be judged during the symposium.
- To cultivate more pharmacoepidemiologists from Asian-Pacific regions by providing opportunities for young researchers to work together and discuss a potential cross-countries project.
- To provide opportunities for young researchers to learn from mentors’ experiences for preparing a cross-countries projects.
- To provide a stage for young researchers to present their proposals, and to acquire the feedbacks from all mentors and audiences.
- To select the best presentation (Rising Investigator) and provide the winner team resources to complete the project.
Introduction of AsPEN: the missions, achievements and strategies of AsPEN
Nam-Kyong Choi, Ehwa Women’s University Korea, Korea
Group 1: Han Eol Jeong, Eunsun Lim, Steven Shen, Jun Ni Ho, Zixuan Wang
Mentors: Nam-Kyong Choi and Nicole Pratt
Group 2: Juliana de Oliveira Costa, Na-Young Jeong, Sungho Bea, Miyuki Hsieh, Jack Janetzki, Adrienne Chan
Mentors: Kenneth Man and Ju-Young Shin
Group 3: Hee-Jin Kim, Dongwon Yoon, Daniel Tsai, Claudia Bruno, Shiori Nishimura, Le Gao
Mentors: Wallis Lau and Edward Lai
Announcement of winner team and rising investigators & Future directions for the AsPEN
Kenneth KC Man, University College London, UK and The University of Hong Kong, Hong Kong
Closing keynote session:
Real-World Evidence Driven Decision Making in Asian Pacific Regions: Current and Future Perspective.
Prof Sallie Pearson
Assoc Prof Bor-Sheng Ko
From 2006 to 2007, he was a visiting research scholar in the Department of Hematology, The University of Texas Health Science Center, Houston, Texas, USA and in the Department of Stem Cell Transplantation and Cellular Therapy, MD Anderson Cancer Center of University of Texas for one year. He was also a joint investigator in National Health Research Institute in Taiwan from 2010 to 2014. From 2013 to 2019, he was assigned as the Secretary-General of Taiwan Society of Blood and marrow Transplantation (TBMT), and was elected as the President of TBMT form 2019 to 2022. He is the president of Taiwan Society of Pharmacoeconomics and Outcome Research (TaSPOR/ISPOR Taiwan Chapter) since 2018, and still the execute director of TBMT.
Asst Prof Krishna Undela
Krishna completed his M.Pharm (Pharmacy Practice) from the National Institute of Pharmaceutical Education and Research (NIPER) Mohali, and his Ph.D. from the JSS Academy of Higher Education & Research, Mysuru. He worked as a Lecturer in the Department of Pharmacy Practice at JSS College of Pharmacy, Mysuru for 8 years. Thereafter he started working as an Assistant Professor in the Department of Pharmacy Practice at NIPER Guwahati. He has taught Pharmacoepidemiology, Pharmacoeconomics, Pharmacovigilance, and Evidence Based Medicine. His areas of research are medication safety in special populations, medication therapy management in cardiology, and evidence synthesis.