AMIA 2026 Annual Symposium Industry Roundtables
Attendees are invited to sign up for one of the following interactive Industry Roundtables, hosted by AMIA’s industry partners. This is an excellent opportunity to learn, share ideas, provide feedback, and engage and collaborate with industry and fellow conference attendees. Lunch is included.*
To express interest in participating, select the roundtable of your choice when you register for the conference. If you have already registered for the conference, you may manage your registration to add the roundtable.
Space is limited, and registering for the roundtable does not guarantee attendance. If you are selected to participate, you will receive confirmation via an invitation from AMIA shortly before the conference.
*Please note: the sponsors of these sessions are not reporting entities in the CMS Open Payments Program. All conference attendees may freely partake in the sponsor-provided food and beverage.
Wolters Kluwer
AI-Enabled Value Set Management as a Semantic Infrastructure for Precision Medicine
November 9, 2026 | 12:20 - 1:50 pm
Join us for an interactive roundtable exploring how AI-enabled value set management can support scalable precision medicine initiatives through semantic abstraction and computable phenotype generation. As healthcare organizations expand pharmacogenomic (PGx) and precision medicine programs, informatics teams are increasingly challenged with harmonizing genomic data with the complex patient context contained within heterogeneous EMR environments. While genomic information such as PGx results can provide valuable clinical insights, it is often not actionable in isolation. Effective precision medicine workflows require additional contextual data including medication exposures, diagnoses, laboratory results, procedures, and longitudinal clinical history. However, organizing clinically relevant information across diverse terminology systems and data sources into computable patient phenotypes and reusable clinical features remains resource intensive and difficult to scale using traditional manual approaches to value set development and maintenance. AI-enabled value set management systems offer a new approach by functioning as a semantic layer capable of organizing heterogeneous clinical data into scalable, reusable computable phenotypes that support clinical decision support, predictive analytics, and precision medicine workflows. This session will explore practical strategies for leveraging AI-assisted value set and terminology management as a semantic abstraction platform for generating computable phenotypes that reduce barriers to cross-institutional precision medicine adoption while improving scalability, interoperability, and governance.
Register now or add to your existing registration
Target Audience
CIOs, CMOs, CMIOs, Chief Analytics Officers, Chief Research Officers, Chief Data Officers, Population Health Leaders, VPs/Directors of Digital Health Platforms, and anyone passionate about healthcare data quality, value set curation, and analytics enablement.
Moderator
Shobha Phansalkar, RPh, PhD, FAMIA
VP,
Client Solutions and Innovation at Wolters Kluwer, Health Language
Leap of Faith Technologies, LLC
From Clinical Intent to Trustworthy AI: Validating IPI and LIPI Across Care, Research, and Education
November 9, 2026 | 12:20 - 1:50 pm
Artificial intelligence in healthcare is only as trustworthy as the clinical information available to it. Yet much of the meaning originally documented by clinicians can be diminished as data moves through normalization, standardization, and analytic pipelines. This roundtable will explore how the Intelligent Phenotype Index (IPI) and the Longitudinal Intelligent Patient-Centric Phenotype (LIPI) can preserve and organize clinical intent to create a more complete, longitudinal, and explainable representation of the patient.
Participants will examine evidence from an OMOP implementation in which direct mapping of interface terminology to SNOMED CT produced a 4.4-fold increase in distinct standard condition concepts from the same source data, including identification of patients who were not captured through conventional phenotyping approaches. The discussion will move beyond the technical results to consider how these capabilities should be validated in real-world clinical, research, and educational settings.
Working with a small group of healthcare executives, clinical informaticians, researchers, and educators, the roundtable will explore several potential validation pathways, including medication reconciliation, longitudinal patient phenotyping, clinical and research cohort identification, and the grounding of AI systems in traceable clinical evidence. Participants will be invited to identify additional high-value use cases and help define the evidence required for clinical and organizational adoption.
The session will also explore the potential for IPI and LIPI to serve as training and capstone platforms in medical and nursing education. By allowing learners to work with longitudinal, clinically meaningful patient representations, these tools could support education in clinical reasoning, informatics, medication management, data interpretation, and the responsible use of AI. The roundtable will invite educators and healthcare leaders to help define how such approaches could be evaluated within medical school, nursing, residency, and other health-professions training programs.
The goal of the roundtable is not simply to present a new technology, but to engage healthcare leaders in defining how IPI and LIPI can be independently evaluated, validated, and applied as foundational infrastructure for trustworthy clinical AI and as tools for educating the next generation of healthcare professionals.
Register now or add to your existing registration
Target Audience
CIOs, CMIOs, Chief Medical Officers, Chief Nursing Informatics Officers, Chief Data and Analytics Officers, Chief Pharmacy Officers, population health leaders, clinical informatics directors, medication-management and pharmacy informatics specialists, EHR and digital-health platform executives, AI and data-governance leaders, and clinical researchers.
Moderators
Frank Naeymi-Rad, PhD, MBA
Executive Chairman, Leap of Faith Technologies, LLC
Evan T. Sholle, MS
Associate Director, Research Informatics Data Science Services, Weill Cornell Medicine
Curtis Cole, MD
Chief Global Information Officer, Associate Professor, Cornell University
