2024 - AR-BIC Conference

2024 Conference Agenda

Real-World Impact of AI

Monday, 2/26:

10:30 am-12 pm: Pre-Conference Workshop A: AWS HealthOmics by AWS
Instructor: Nan Gabriel
Workshop Description: This workshop focuses on using the Graphical User in AWS Console to complete tasks and demonstrate the capabilities of AWS HealthOmics Storage and Ready2Run Workflows. Some experience with AWS, genomics data types, and genomics data analysis is expected but not a strict requirement.

10:30 am-12 pm: Pre-Conference Workshop B: Cloud-based Training modules for Data Sciences

Instructor: Dr. Stephanie Byrum
Workshop Description: This workshop will introduce the NIGMS Sandbox cloud based training modules, how to setup an account, create a compute engine using Google cloud, and access 12 different data science training modules. A working demonstration of the Biomedical Imaging Analysis training module will be presented.

10:30 am -12 pm: Pre-Conference Workshop C: AI and Machine Learning Made Easy With JMP:
Instructor: Dr. Russ Wolfinger and Dr. Wenjun Bao
Workshop Description: This workshop features new developments in JMP Pro software to provide you direct access to two of the most powerful libraries for AI and Machine Learning: Torch and XGBoost. The primary motivation is to enable busy scientists and engineers to interactively and quickly wrangle data and build state-of-the-art predictive models without having to write code in Python or R. This often affords dramatic gains in efficiency in understanding, predicting, and explaining complex scientific systems, leading to better discoveries and progress and mastery of difficulties like overfitting and deployment. The dynamic graphical interfaces and workflows are designed from deep experience gained and battle tested over years engaging with a worldwide customer base and in dozens of data science competitions. We show examples from a variety of scientific fields using image, text, and tabular data.

10 am-1 pm: Registration and Poster Setup

2-2:15 pm: Opening Remarks
Speakers: TBA

2:15-5:30 pm: Plenary Session
Speakers:

Thomas Hartung, MD PhD, is the Doerenkamp-Zbinden-Chair for Evidence-based Toxicology in the Department of Environmental Health and Engineering at Johns Hopkins Bloomberg School of Public Health and the Whiting School of Engineering, Baltimore. He also holds a joint appointment for Molecular Microbiology and Immunology at the Bloomberg School. He is adjunct affiliate professor at Georgetown University, Washington D.C.. In addition, he holds a joint appointment as Professor for Pharmacology and Toxicology at University of Konstanz, Germany; he also is Director of Centers for Alternatives to Animal Testing (CAAT, http://caat.jhsph.edu) of both universities. CAAT hosts the secretariat of the Evidence-based Toxicology Collaboration (http://www.ebtox.org) and manages collaborative programs on Good Read-Across Practice, Good Cell Culture Practice, Green Toxicology, Developmental Neurotoxicity, Developmental Immunotoxicity, Microphysiological Systems and Refinement. As PI, he headed the Human Toxome project funded as an NIH Transformative Research Grant and the series of annual Microphysiological Systems World Summits starting in 2022 by 60+ organizations. He is Field Chief Editor of Frontiers in Artificial Intelligence. He is the former Head of the European Commission’s Center for the Validation of Alternative Methods (ECVAM), Ispra, Italy, and has authored more than 630 scientific publications with more than 43,000 citations (h-index 109). His toxicology classes on COURSERA had almost 17,000 active learners.

Ruth Roberts, PhD is Chair and Director of Drug Discovery at Birmingham University, UK and is Cofounder of ApconiX, an integrated toxicology and ion channel company. Before that Dr. Roberts was Global Head of Regulatory Safety at AstraZeneca (2004-2014) and Director of Toxicology for Aventis in Paris, France (2002-2004). Dr. Roberts is current Chair of the HESI board of Trustees, has served on SOT council and is past president of EUROTOX, the British Toxicology Society (BTS) and of the Academy of Toxicological Sciences (ATS). Dr. Roberts was the recipient of the SOT Achievement award in 2002, the EUROTOX Bo Holmstedt Award in 2009, the SOT Founders award in 2018 and is the recipient of the 2022 ATS Millie Award, given for outstanding achievement. ApconiX recently received the 2022 Queen’s Award for Enterprise. With more than 150 publications in peer-reviewed journals, Dr. Roberts is committed to developing and implementing science-led approaches to drug discovery and development.

Shuk-Mei Ho, PhD, is Professor in Department of Pharmacology and Toxicology and Vic e Chancellor for Research & Innovation at University of Arkansas for Medical Sciences. Dr. Ho received bachelor’s and doctoral degrees from University of Hong Kong and her postdoctoral training in Boston University. Her research interests focus on the role of endocrine disruptors and hormones and the interplay between genetics and epigenetics. She has published more than 300 articles, pioneering the fields of environmental epigenetics and developmental origins of adult disease. Her highly innovative work has advanced basic science research and led to meaningful changes in public health and medical practices on the national and global level.

Li Shen, PhD, is Professor and Deputy Director of Division of Informatics in the Department of Biostatistics, Epidemiology and Informatics at the Perelman School of Medicine in the University of Pennsylvania. He serves as the Associate Director for Bioinformatics at the IBI and the Faculty Director of the IBI Bioinformatics Core. He obtained his Ph.D. degree in Computer Science from Dartmouth College. His research interests include medical image computing, biomedical informatics, machine learning, network science, imaging genomics, multi-omics and systems biology, Alzheimer’s disease, and big data science in biomedicine. He is a fellow of AIMBE, a distinguished member of ACM, and a distinguished contributor of IEEE Computer Society.

6-8 pm: Welcome Reception & Poster Session

8-9 am: Breakfast, Networking, and Career Development Roundtables

Roundtable Discussion A: Careers in Medicine – join Dr. Bobby McGehee to learn the ins and outs of medical school applications, admissions, and experience.

Roundtable Discussion B: Careers at the FDA – join Dr. Tucker Patterson to learn about the vast career opportunities within the FDA, the world’s premier regulatory agency for public health and safety.

9-10:30 am: Breakout Session 1: AI for Analyzing Unstructured Data
Chair: Dr. Huixiao Hong

Speakers: Dr. Wenjun Bao, Dr. Fan Dong, Dr. Wenjing Guo, & Dr. Magnus Gray
Session Description: Unstructured data refers to data that doesn’t have a predefined structure or format, such as text documents, images, audio recordings, and videos. Analyzing unstructured data is a common and valuable application of artificial intelligence (AI). AI can be used to extract meaningful insights, patterns, and knowledge from unstructured data. When analyzing unstructured data, it’s essential to use the appropriate AI techniques and tools based on the specific requirements of projects or business goals. Recently, many AI techniques and approaches have been emerging for analyzing unstructured data, including natural language processing techniques that enable the analysis of text data, such as BERT, GPT-3 and their successors which are proficient at tasks such as text classification and summarization; sentiment analysis AI techniques that determine the emotional tone or sentiment expressed in textual data to assist gauge public opinion and customer feedback; text mining and information retrieval approaches that extract valuable information from large volumes of text data, such as keyword extraction, topic modeling, and document clustering; and named entity recognition methods that identify and classify entities such as drug terms, genes, and proteins within unstructured text. This session provides a lineup of experts in application of AI for analyzing unstructured data to share their research, findings, and opinions and to discuss the possibility and likelihood of advancing AI techniques and approaches to promote and improve analysis of unstructured data.

9-10:30 am: Breakout Session 2: AI Ethics: Considerations and Recommendations for Pursuing Positive Impact
Chair: Dr. Samantha Robinson
Speakers: Dr. Leihong Wu, Dr. Zachary Stine, & Dr. David Barrett

Session Description: Following the recent release of ChatGPT, Bard, and Bing Chat, debate and discussion about artificial intelligence (AI) ethics has broadened in scope. The risks posed by new AI applications are risks that are now being faced head on by government, industry, and academia. Everywhere that has embraced the rapid development, and the utility of AI must also carefully consider the ethical implications of its use. With recent technological advancements and the increasing availability of real-world data, there is widespread consensus that discussions about AI ethics must move beyond explainability/interpretability and fairness/bias.
AI is one of the most impactful technologies developed but, without consideration of the problems existent in present-day AI applications and concerted efforts to find solutions to these problems, the safety of AI (especially in high-stakes settings) will remain uncertain. This session will serve as a forum for scientists, educators, philosophers, and practitioners from across our state to share insights about AI ethics and discuss how, with ethics in mind, we can harness the power of AI for the public good.

11am-12:30 pm: Breakout Session 3: AI in Informatics
Chairs: Dr. Mary Yang & Dr. John Talburt

Speakers: Dr. Xiaowei Xu, Dr. Hadi Salman, Dr. Cesar Compadre, & Dr. Mariofanna Milanova
Session Description: In this era of data abundance and rapid advancements in Artificial Intelligence (AI) technologies, the dynamic synergy between AI and informatics has emerged as a driving force for profound breakthroughs. Across the multifaceted landscape, encompassing Bioinformatics, Health Informatics, Information Quality, and Toxicological Informatics, and extending beyond, AI has risen as a potent catalyst, reshaping our comprehension, expanding our capabilities, and magnifying our overall impact. In this session, we will unveil the boundless potential of AI in various informatics domains, exploring AI’s transformative capabilities and its potential to tackle critical challenges in informatics while driving innovations. It serves as a platform for collaboration and networking, facilitating opportunities that arise when diverse informatics fields converge with AI technologies.

11am-12:30 pm: Breakout Session 4: Interpretable AI: Data Driven and Mechanistic Modeling
Chair: Dr. Hao Zhu

Speakers: Dr. Fred Prior, Dr. Ting Li, & Dr. Alex Maertens
Session Description: Addressing the safety aspects of new chemicals has historically been undertaken through animal testing studies, which are expensive and time-consuming. Computational toxicology is a promising alternative approach that utilizes machine learning (ML) and deep learning (DL) techniques to predict toxicity potentials of chemicals. Although the applications of ML and DL based computational models in chemicals toxicity predictions are attractive, many toxicity models are “black box” in nature and difficult to interpret by toxicologists, which hampers the chemical risk assessments using these models. The recent progress of interpretable ML (IML) in the computer science field meets this urgent need to unveil the underlying toxicity mechanisms and elucidate domain knowledge of toxicity models. In this new modeling framework, the toxicity feature data, model interpretation methods, and the use of toxicity knowledgebase in IML development advance the applications of computational models in chemical risk assessments. The challenges and future directions of IML modeling in toxicology are strongly driven by heterogenous big data and newly revealed toxicity mechanisms. The big data mining, analysis, and mechanistic modeling using IML methods will advance artificial intelligence in the big data era to pave the road to future computational chemical toxicology and will have a significant impact on the risk assessment procedure and public health.

2-2:45 pm: Dialogue with FDA Chief Scientist and NIEHS/NTP Director
Speakers: Dr. Namandjé N. Bumpus & Dr. Richard Woychik

2:45 – 3:30 pm: Panel Discussion
Moderator: Dr. Weida Tong
Panelists: Dr. William Slikker, Jerry Adams, & Dr. Shraddha Thakkar

3:30 – 4 pm: Award Announcements and Concluding Remarks