2025 Conference Agenda

Challenges and Opportunities in AI-Driven Healthcare and Generative Models

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Presenters

May Dongmei Wang, Ph.D., Wallace H. Coulter Distinguished Faculty Fellow
Professor of BME, ECE, CSE Georgia Institute of Technology and Emory University

Presentation Materials

Link to publicly available materials (e.g. presentation slides, workshop documents, etc).

AI in FDA: Opportunities and Challenges

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Presenters

Tucker Patterson, Ph.D., Director, FDA/National Center for Toxicological Research

Presentation Materials

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EHR Research and In Silico Approaches to Advance Precision Medicine and Enhance Drug Safety

Description of the session can go here. Lorem ipsum dolor sit amet consectetur adipiscing elit dapibus duis, nisi fames suspendisse magnis blandit quis gravida euismod cursus, molestie ac nam libero curabitur ultrices parturient diam. Vulputate aliquet nunc ornare fusce leo mus egestas eleifend, torquent varius fermentum penatibus rutrum sagittis mattis, dictumst taciti velit congue nibh class dis.

Presenters

Ayako Suzuki, M.D., Ph.D., Associate Professor of Gastroenterology, Duke University

Presentation Materials

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AI-derived Prognostic Covariates and Enrichment Strategy Substantially Increase the Efficiency of Clinical Trials

Description of the session can go here. Lorem ipsum dolor sit amet consectetur adipiscing elit dapibus duis, nisi fames suspendisse magnis blandit quis gravida euismod cursus, molestie ac nam libero curabitur ultrices parturient diam. Vulputate aliquet nunc ornare fusce leo mus egestas eleifend, torquent varius fermentum penatibus rutrum sagittis mattis, dictumst taciti velit congue nibh class dis.

Presenters

Viswanath Devanarayan, Ph.D., Head of Clinical Data Science, Eisai Inc.; Adjunct Professor, University of Illinois Chicago

Presentation Materials

Link to publicly available materials (e.g. presentation slides, workshop documents, etc).

Generative AI for Drug Safety and Toxicology

AI encompasses two main application categories: predictive and generative. Predictive algorithms utilize existing data to forecast future outcomes, whereas generative algorithms generate new data through AI-driven learning. Generative Artificial Intelligence (AI), exemplified by technologies like ChatGPT, has captured public attention with its vast potential across various fields. The wide range of Generative AI (GenAI) approaches offers unprecedented opportunities for enhancing strategies to predict toxicity. This session will showcase examples from FDA/NCTR projects in GenAI using the wide range of GenAI approaches to evaluate drug safety and toxicology. The topics will include:

1. Using LLMs for toxicity classification
2. Learning from existing animal study data to generate animal study results without conducting actual experiments
3. Developing knowledge-based prediction with GenAI
4. Translate findings from one organ to another

Co-Chairs

Weida Tong and Leihong Wu, Division of Bioinformatics and Biostatistics, FDA/NCTR

Presenters

Leihong Wu, Division of Bioinformatics and Biostatistics, FDA/NCTR
Adverse Event (AE) classification with GenAI

Ting Li  Division of Bioinformatics and Biostatistics, FDA/NCTR
DeepDILI

Xi Chen, Division of Bioinformatics and Biostatistics, FDA/NCTR
AnimalGAN vs QSARs

Dongying Li, Division of Bioinformatics and Biostatistics, FDA/NCTR
QKAR vs QSARs in Drug-induced Cardiotoxicity

Presentation Materials

Link to publicly available materials (e.g. presentation slides, workshop documents, etc).

From Hogs to Algorithms: AI’s Impact on Teaching in the Land of Opportunity

In this session, we will discuss the use of artificial intelligence and machine learning in university education in Arkansas. There will be three professors discussing how they use AI in teaching, and three students giving brief talks about their experiences in using AI in the classroom and their work.

David Ussery (UAMS) will talk about how machines learn, and what we can learn from this, with examples from more than 40 years of machine learning in bioinformatics; Brian Delevan (Arkansas Department of Health) will discuss how he’s using machine learning to map outbreaks in Arkansas. Samantha Robinson (UAF/UADA) will discuss the use of machine learning and AI in teaching statistics and data science to undergraduates, followed by one of her students.  Don Jonson (UA) will discuss using AI tools in Agricultural Education, followed by one of his students.

Co-Chairs

Samantha Robinson, Associate Professor, UAF/UADA

David Ussery, Professor, UAMS

Presenters

David Ussery, Professor, UAMS

Brian Delevan, AR Dept. of Health, Ph.D. student in the UALR/UAMS Bioinformatics Program

Samantha Robinson, Associate Professor, UAF/UADA

Don Johnson, UAF

Presentation Materials

Link to publicly available materials (e.g. presentation slides, workshop documents, etc).

Advancing Regulatory Science with Digital Innovations

The integration of digital technologies into regulatory science is transforming compliance processes and decision-making in the life sciences and healthcare sectors. This paradigm shift is driven by data-centric approaches enabling real-time analysis and improved compliance monitoring, while Regulatory Technology and cloud solutions automate tasks, enhance risk management, and facilitate global collaboration.

This session highlights how Artificial Intelligence (AI), machine learning, and digital health technologies are reshaping real-world data validation, pharmacovigilance, and regulatory frameworks. A key focus is the critical transition from proof of concept to enterprise solutions, crucial for validating innovations, mitigating risks, and achieving scalable implementations that transform regulatory processes organization-wide.

The session will explore how collaboration plays a pivotal role in this transformation by integrating regulatory science into interdisciplinary research. Participants will gain insights into creating a responsive and efficient regulatory landscape, equipping them with knowledge to navigate the evolving environment in life sciences and healthcare. Researchers will learn strategies for incorporating regulatory considerations.

Chair

Shraddha Thakkar, FDA/CDER

Presenters

Huixiao Hong, Division of Bioinformatics and Biostatistics, FDA/NCTR

Joshua Xu, Division of Bioinformatics and Biostatistics, FDA/NCTR

Dong Wang, Division of Bioinformatics and Biostatistics, FDA/NCTR

Morgan Carrasquillo, Informatics and Business Operations Staff, FDA

Presentation Materials

Link to publicly available materials (e.g. presentation slides, workshop documents, etc).

Applications of Micro-Computed Tomography and Spatial Technologies in Anatomical Sciences, Biomedical Research, and Beyond

Since 2018, the University of Arkansas MicroCT Imaging Consortium for Research and Outreach (MICRO), which is nested within the Center for Advanced Spatial Technologies (CAST), has been providing researchers with the ability to non-destructively document the structure of a range of natural and engineered materials in extremely fine three-dimensional detail. This imaging enables the systematic evaluation of composition, form, and functional properties of a wide variety of objects, leading to breakthroughs in anatomical, biomedical, and engineering sciences. This session will provide an overview of microCT imaging applications and highlight ongoing research using microCT data as well as spatial data more broadly.

Chair

Claire Terhune, Associate Professor of (ARSC)-Arts & Sciences, Director of Graduate Studies, University of Arkansas

Presenters

Claire Terhune

Kathleen Paul

Sam Stephens and Morten Jensen

Parker Taylor

Carla Klehm

Presentation Materials

Link to publicly available materials (e.g. presentation slides, workshop documents, etc).

Next Generation Sequencing Approaches Across the Biological Spectrum

The proposed session will explore next generation sequencing (NGS) technologies and their applications across the biological spectrum.  Session speakers have extensive experience using a range of sequencing platforms for different uses including the study of microbial organisms as well as understanding the role of genetic mutations in human diseases including cancer and genetic disorders.  The session’s featured speaker from the University of Arkansas, Dr. Christopher Nelson, utilizes long-read sequencing approaches to evaluate approaches for the development of cures for genetic diseases such as muscular dystrophy.  Other session speakers including Dr. Javier Revollo from the FDA-NCTR will discuss the evaluation of NGS approaches to assess rare genetic mutations that can lead to cancer development.  Dr. David Ussery from UAMS will discuss the use of accessible NGS approaches to assess the genetics of microbial pathogens.  The final presentation by Dr. Kristina Feye will focus on cross-NGS platform comparisons describing their utility for different plasmid and bacterial genomic applications.  Each of the available NGS technologies have strengths and weaknesses for different applications across the biological spectrum and their developments have led to a paramount shift in moving our understanding of genetics forward with the promise of limiting and/or curing diseases that impact humanity.

Chair

Steven Foley, FDA/CDER

Presenters

Christopher Nelson, University of Arkansas
Third generation sequencing methods for examining CRISPR therapy safety

David Ussery, University of Arkansas for Medical Sciences
The democratization of NGS via nanopore sequencing and its portability

Javier Revollo, FDA National Center for Toxicological Research
Approaches for error-corrected NGS to assess genetic mutations

Kristina Feye, FDA National Center for Toxicological Research
Cross-platform comparisons for plasmids/bacterial genomes

Presentation Materials

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Transformative Technologies for Integrative Health

The University of Arkansas in Fayetteville has launched the Institute for Integrative and Innovative Research (I³R, pronounced:  “I-cubed-R”), which is designed to pioneer solutions to wicked problems through innovation and convergence across sectors. Its initial focus is to take on the Grand Challenge of Integrative Health with an approach that recognizes the multiple physiological, social, and environmental factors at play and an approach that utilizes a holistic and integrative strategy to produce impactful solutions that are deployable at scale. This session will describe some of the on-going and planned research and development at I³R, with an emphasis on the role of data-driven approaches, AI and machine learning, and biotechnology. With I³R’s commitment to convergence, the session will also seek to connect with innovators from across the state to form partnerships that will enable healthier living and improve health for all Arkansans.

Chair

Claire Terhune, Associate Professor of (ARSC)-Arts & Sciences, Director of Graduate Studies, University of Arkansas

Presenters

Meredith Adkins, PhD, I³R, UA Fayetteville
Transformative Technologies for Food Systems

Prashant Ravishankar, PhD, and Philip Sambol, I³R, UA Fayetteville
Transformative Technologies for Agrifood Biotech

Alejandro Martin Gomez, PhD, I³R and Department of Electrical Engineering and Computer Science (EECS), UA Fayetteville
Machine Learning and Extended Reality for Surgical Procedures

James Abbas, PhD, I³R and Department of Biomedical Engineering, UA Fayetteville
Data-driven Approaches to Personalizing Neurostimulation

Presentation Materials

Link to publicly available materials (e.g. presentation slides, workshop documents, etc).