2025 SCIENCE OF PATIENT ENGAGEMENT SYMPOSIUM 
“ELEVATING INNOVATION: MEDICINE, MEDTECH, AND AI” 

The National Health Council’s (NHC’s) Science of Patient Engagement Symposium was held on May 7 and 8, 2025, at the National Press Club in Washington, DC. This year’s Symposium brought together more than 180 leaders from patient organizations, non-profit groups, industry, academia, and government to discuss how patients, their families, and caregivers can better provide insights at all stages of development for a new drug, treatment, or technology, and how researchers and product developers can integrate these insights into practical and innovative solutions to meet the needs of a wide array of patients. 

The following are highlights of the two-day event. 

DAY ONE 

WELCOME AND INTRODUCTIONS 

• • Randall Rutta, MA, Chief Executive Officer, National Health Council 
  • Omar A. Escontrías, DrPH, MPH, Senior Vice President of Equity, Research, & Programs, National Health Council 

In their opening remarks, Mr. Rutta and Dr. Escontrías welcomed attendees, thanked the event sponsors and panelists, and laid out the key objectives of this year’s Symposium: to collaborate with key experts; to apply practical tools; and to identify tactics and opportunities that help ensure patients are and remain top of mind as machine learning and artificial intelligence technologies continue to develop. 

Mr. Rutta noted that this year’s Symposium, now in its eighth year, builds on a rich tradition of engaging patients to get the best results in health care, and this year, at this moment, the theme of the Symposium is particularly compelling.  Meaningful patient engagement is essential, and in this current environment the patient community needs to be an active part of that to ensure patients are recognized as equal partners. 

KEYNOTE REMARKS: The SCIENCE OF PATIENT ENGAGEMENT IN AN ERA OF CHAOTIC CHANGE   

• • Nicholas Webb, Number One Best Selling Author & Chief Executive Officer, LeaderLogic, LLC 

Session Summary

Mr. Webb opened his session by posing the critical question: “What is the future of health care?” He argued that the answer lies in embracing chaotic innovation and understanding how emerging technologies—particularly robotic automation and multimodal AI—intersect with “consumerized” patient engagement models. Webb emphasized that successful organizations are leaning into this change, not resisting it, and focusing on delivering quality, safe, and effective care. Central to his message was the idea that patient engagement should be seen through the lens of health care consumerism. To truly engage patients, health care systems must address what patients dislike, emphasize what they value, and personalize their experiences. He outlined three guiding concepts: the expectation baseline, patient journey mapping, and the patient value saga. Each plays a critical role in improving patient experiences and outcomes, particularly when supported by AI and other innovative technologies. Webb closed by urging the audience to remain open to AI’s potential, especially its ability to reduce costs and improve access to care.

Key Takeaways

• • Patient as Consumer: Viewing patients as consumers helps health care systems better meet expectations and improve experiences.
  • Expectation Baseline: Understanding what patients love, hate, and expect is key to enhancing engagement and value.
  • Simplified Journeys: Mapping the patient journey through clear personas improves navigation and advocacy.
  • AI Integration: Emerging tools like multimodal AI can personalize care, cut costs, and boost access.
  • Openness to Innovation: Embracing new technologies is critical to staying relevant and effective in modern health care.

SESSION 1: TEAMWORK MAKES THE DREAM WORK – BRIDGING THE GAP BETWEEN MEDTECH AND PATIENT NEEDS  

 Moderator:  

• • Karl Cooper, Esq., Executive Director, American Association on Health and Disability  

Panelists: 

• • Juan Carlos Espinoza Salomon, MD, Chief Research Informatics Officer, Stanley Manne Children’s Research Institute, Lurie Children’s Hospital 
  • Scott Whitaker, President and Chief Executive Officer, AdvaMed® 
  • Christine Waggoner, Chief Executive Officer & Co-Founder, Cure GM1 Foundation  

Session Summary

This panel explored how to bridge the gap between medical technology (MedTech) innovation and real patient needs, particularly by involving patients and caregivers earlier and more meaningfully in the development process. Panelists highlighted barriers such as the lack of resources for rare diseases, regulatory hurdles, and the need for better data infrastructure. They also emphasized the importance of collaboration across industry, advocacy, and clinical stakeholders to create more inclusive, responsive, and impactful medical technologies.

Key Takeaways

• • Early Patient Involvement: Engaging patients and caregivers at the earliest stages of MedTech development—before clinical trials—can lead to more relevant, usable technologies.
  • Rare Disease Challenges: The MedTech system struggles to serve rare diseases due to high development costs and limited market incentives.
  • Data Infrastructure Gaps: Small advocacy groups often bear the burden of building patient registries, yet they lack the resources for comprehensive, sustainable data collection.
  • Real-World Evidence: Using real-world data for labeling expansion offers a practical path to reflect off-label use and improve access.
  • Collaboration & Interoperability: Greater cross-sector cooperation and a shift toward interoperable technologies are essential for transforming MedTech’s clinical impact.

SESSION 2: INTEGRATING PRECISION MEDICINE AND HEALTH SYSTEMS INTO AI INNOVATION  

Moderator: 

• • Richard Sperry, Chief Strategy Officer, GBS | CIDP Foundation International 

Speaker: 

• • Raj Ratwani, PhD, Vice President of Scientific Affairs, MedStar Health Research Institute, Director, MedStar Health National Center for Human Factors in Healthcare, Professor, Georgetown University School of Medicine 

Session Summary

This session highlighted how AI is transforming health care operations and clinical care, from improving diagnosis and administrative workflows to enhancing patient engagement and safety. Dr. Ratwani discussed the promise of AI-human collaboration and stressed the importance of ethical implementation guided by fairness, equity, and transparency. While AI offers significant benefits, it also presents real challenges around safety, bias, governance, and cost—challenges that must be addressed with active input from the patient advocacy community.

Key Takeaways

• • AI in Practice: AI is currently used in clinical decision support, practice efficiency, virtual care, and administrative tasks like billing and prior authorizations.
  • Ethical Use Matters: Ensuring AI is fair, appropriate, valuable, equitable, and safe is critical to building trust and minimizing harm.
  • AI-Human Teaming: Combining the strengths of humans and machines is key to safer, more effective care.
  • Major Challenges: Health systems face steep barriers, including limited safeguards, lack of governance structures, high costs, and no reimbursement model.
  • Role of Advocates: The patient advocacy community plays a vital role in shaping responsible, patient-centered AI use in health care.

SESSION 3: FROM DATA TO DIAGNOSIS AND PREDICTION – AI’S GREATEST HITS  

Moderator: 

• • Charity Watkins, PhD, MSW, Assistant Professor, Department of Social Work, North Carolina Central University, BIRCWH Scholar, Department of Gynecology and Obstetrics, Duke University School of Medicine 

Panelists: 

• • Christian Rubio, MBA, MA, Executive Director, EverythingALS 
  • Federico Asch, MD, FACC, FASE, Director of the Echocardiography Core Lab, MedStar Health Research Institute, Associate Professor of Medicine (Cardiology), Georgetown University  

Session Summary

This session focused on how AI is being applied to detect and manage chronic diseases, including heart disease and ALS, through real-world case studies. Panelists emphasized AI’s potential to improve diagnostic accuracy, efficiency, and accessibility, especially in underserved communities. They also discussed the importance of patient-centered design, data stewardship, and the systemic barriers limiting AI’s full integration into health care. The conversation underscored that successful AI in medicine requires collaboration, ethical data use, and intentional, inclusive design.

Key Takeaways

• • AI in Chronic Disease: AI improves efficiency and accuracy in diagnosing and managing diseases like heart conditions and ALS, especially via imaging and predictive tools.
  • Citizen-Led Innovation: Patient-driven models, like EverythingALS, are creating personalized predictive tools and trial networks to address gaps in traditional research approaches.
  • Patient-Centered Design: Patients and caregivers must be involved from the start in designing AI tools to ensure usability, clarity, and meaningful engagement.
  • Data Stewardship: Transparency and consent are critical. Patients should retain ownership of their data, with organizations serving as responsible stewards.
  • Barriers to Adoption: Lack of alignment between innovation, regulation, and public health goals—along with insufficient collaboration—continues to hinder AI’s widespread use in health care.

CLOSING REMARKS  

• • Devin Jopp, EdD, Chief Executive Officer, Association of Professionals in Infection Control and Epidemiology 

In his brief closing remarks, Dr. Jopp observed that the optimism in the room was palpable and powerful, and while he acknowledged the collective concern about the potential downsides of AI and machine learning, he hoped the attendees would use that optimism to empower, embrace, and drive patient engagement.  He challenged the attendees to think about how best to work together to make sure the power of partnership happens, to leverage their collective might, and to actualize all the knowledge and insights shared throughout the day. 

DAY TWO 

Remarks by: 

• • Irene O. Aninye, PhD, Chief Science Officer, Society for Women’s Health Research 

Dr. Aninye opened Day Two by recapping the topics covered on Day One: patient engagement and resilience in era of chaotic change; co-creation of med-tech and medical devices; and how AI has shifted research, diagnosis, and treatment for cardiovascular disease and ALS. She noted how the attendees and speakers started to ask each other tough questions, such as: How do we harness the full potential of data and AI in ways that are ethical, inclusive, and responsive to real world patient and caregiver needs?  How do we ensure that emerging technologies protect patient rights rather than outpace them? And how do we move beyond pilot projects and promising ideas to sustainable impact at scale?  She encouraged the audience to build on yesterday’s momentum, to keep pushing towards innovation that is not only patient-centered but truly transformative, and to find connections that can make an impact on sustainable and transformative changes in health care.

KEYNOTE: PUTTING PATIENTS FIRST IN DRUG DISCOVERY, A FEW AI-DRIVEN CASE STUDIES  

Moderator: 

• • Irene O. Aninye, PhD, Chief Science Officer, Society for Women’s Health Research 

Speaker: 

• • Petrina Kamya, PhD, Head of AI Platforms and President, Insilico Medicine Canada 

Session Summary

Dr. Kamya detailed how Insilico Medicine is using AI to transform drug discovery and development by reducing costs, improving efficiency, and increasing the likelihood of clinical success. She shared case studies demonstrating how the company’s AI-driven platforms have accelerated pre-clinical timelines and uncovered novel therapeutic targets for diseases like ALS and endometriosis. Emphasizing transparency and collaboration, Dr. Kamya highlighted the critical role of patient advocacy, clear communication, and trust in advancing AI-driven innovations in medicine—while dispelling myths around the capabilities and limits of AI in drug development.

Key Takeaways

• • Accelerating Drug Development: Insilico has reduced pre-clinical timelines from 5 years to 1.5 years and costs from $700M to $2.6M using AI, demonstrating successful results in diseases with limited treatment options.
  • AI for Repurposing and Discovery: Platforms like PandaOmics enable the identification of novel disease targets and repurposed drugs for faster clinical deployment, as shown in ALS and endometriosis case studies.
  • Transparency Builds Trust: Insilico fosters trust by openly sharing its tools, methodologies, and outcomes—both successes and failures—with the broader scientific and patient community.
  • Patient Advocacy Matters: Engagement with patient groups helps foster understanding and acceptance of AI-developed therapies, improving patient compliance, and reducing skepticism.
  • AI is Not a Magic Button: Despite impressive advances, AI tools are decision-support systems—not drug generators. Human expertise remains essential to interpret and act on AI output.

SESSION 4: ARE WE SPEAKING THE SAME LANGUAGE? WHEN SMART RECORDS AND STRONGER VOCIES AMPLIFY PATIENT POWER  

Moderator: 

• • Jennifer Berson, MSEd, Migraine and Headache Disorders Patient Advocate 

Panelists: 

• • Erkan Hassan, PharmD, FCCM, Founder and Chief Executive Officer, Transformational Views Consulting Group, Inc. 
  • Glenna Crooks, PhD, Founder and Chief Executive Officer, Strategic Health Policy International, Inc. 
  • Katie McCurdy, Founder, Pictal Health  

Session Summary

This session explored how AI and design thinking can be used to harness patient data from electronic health records and lived experiences to improve health outcomes. Panelists discussed tools to help patients communicate their stories, ethical considerations for AI in medicine, and how AI can enhance clinical decision-making beyond traditional settings. The conversation emphasized the importance of co-defining problems with patients, building trust, and maintaining human connection alongside technological innovation.

Key Takeaways

• • Patient Storytelling Enhances Care: Tools like Pictal Health’s visual health timeline help patients articulate complex medical histories and support more informed, empathetic care by providers.
  • AI Trust Requires Transparency: Many physicians are conflicted about using AI; building trust with patients means clearly disclosing its use and ensuring accountability among developers and clinicians.
  • Technology Must Serve the Problem, Not Vice Versa: Effective innovation starts with co-defining real patient challenges—not chasing AI for its own sake.
  • Personalized Medicine is the Future: AI can integrate clinical, genomic, and social data to tailor treatment plans and monitor care, reducing over- and under-treatment.
  • Human Connection Still Matters: While AI can be empathetic, it must not replace in-person, human care—which remains essential to patient trust and well-being.

SESSION 5: DATA AT THE SPEED OF CARE: ENGINEERING UNIVERSAL ACCESS  

Moderator: 

• • Steph McCoy, Founder & Patient Advocate, Bold Blind Beauty 

Panelists: 

• • Gina Assaf, Co-Founder & Co-Lead, Patient-Led Research Collaborative  
  • Megan Freed, MPH, Chief of Strategic Initiatives, Parent Project Muscular Dystrophy  

Session Summary

This session focused on the importance of co-creating representative, patient-centered data that informs AI and machine learning technologies to advance equitable and effective health care. Panelists discussed their approaches to capturing and leveraging patient experiences, especially those traditionally overlooked, by building trust, reducing participation barriers, and ensuring data ownership. Strategies for inclusive data collection, re-engagement, and ethical data use were highlighted, with a strong emphasis on treating patients as equal partners in research and innovation.

Key Takeaways

• • Representation Starts with Lived Experience: True representation requires engaging diverse patient communities and designing data collection tools based on real-world experiences and needs.
  • Trust and Accessibility Drive Participation: Removing barriers—such as literacy challenges, device limitations, and fatigue—while being transparent about how data will be used builds trust and boosts engagement.
  • Technology Must Meet Patients Where They Are: Shifting to mobile-friendly platforms and allowing patients to contribute data on their own time greatly improves retention and data completeness.
  • Patients Must Own and Understand Their Data: Empowering patients to access and share their data and ensuring consent forms clarify data rights and sharing practices, are key to ethical data stewardship.
  • Co-Creation is Essential for Impact: Patients should be involved in every stage—from designing surveys to defining outcomes—to ensure the data collected serves their communities and drives meaningful change.

SESSION 6: CHAT IS THIS A REAL PATIENT ENGAGEMENT?  
Moderator: 

• • Aicha Diallo, MPH, CHES, Vice President of Programs, Patient Empowerment Network 

Panelists: 

• • Nicol Turner Lee, PhD, Director & Senior Fellow of Governance Studies, Center for Technology Innovation, Brookings Institution 
  • Heather Flannery, Chief Executive Officer, AI MINDSystems 
  • Susannah Rose, PhD, Executive Director, AI Discovery & Vigilance to Accelerate Innovation & Clinical Excellence; Vice-Chair, Artificial Intelligence Technology (AIT) Committee, Associate Professor, Department of Biomedical Informatics, Vanderbilt University Medical Center  

Session Summary

This session explored the transformative role of artificial intelligence in health care, emphasizing the need to design AI tools that are inclusive, patient-centered, and ethically sound. Panelists discussed their work in data governance, patient advisory groups, and AI evaluation systems, underscoring the importance of community engagement, transparency, and evidence-based development. While AI holds great promise for improving diagnosis, treatment, and care delivery, the panel warned of the risks posed by inequitable implementation, flawed data, and insufficient patient involvement. They called for stronger policy interventions, educational efforts, and partnerships to ensure AI advances health equity and supports informed, empowered patients.

Key Takeaways

• • AI Must Be Patient-Centered by Design: Many AI tools are currently developed with organizational needs in mind, not patient outcomes. Patient voices need to be embedded from the beginning—not as an afterthought.
  • Governance and Transparency Are Critical: Effective data governance systems, patient advisory groups, and transparent evaluation frameworks are essential to ensure AI is used ethically and safely in health care.
  • Equity Requires Infrastructure and Inclusion: Without targeted support, under-resourced providers and medically marginalized communities risk being left behind. Policies must prioritize equitable access and inclusion.
  • Health Literacy Can Be Dynamically Addressed with AI: Modern AI offers new potential to personalize communication and adapt to individuals’ literacy levels in real time—an opportunity that was unimaginable until recently.
  • Excitement Must Be Balanced with Caution: While AI’s potential is vast, the panel urged careful attention to data quality, unintended harms, and the speed of AI deployment, warning against a harmful “arms race” approach.

SESSION 7: FINAL KEYNOTE – HUMAN FLOURISHING IN AN AGE OF HEALTH AI  

Speaker: 

• • Brian Anderson, MD,Chief Executive Officer, Coalition for Health AI (CHAI) 

Session Summary
This session featured Dr. Anderson of CHAI, who outlined efforts to build safe, equitable, and transparent health AI through a structured lifecycle framework and strong community engagement. He emphasized the urgent need for quality assurance infrastructure, greater transparency via “AI Nutrition Labels,” and tools aligned with patient values. With a focus on human flourishing, CHAI envisions agentic AI expanding access in underserved areas—if developed collaboratively and responsibly.

Key Takeaways

• • AI Lifecycle Standards Promote Accountability: CHAI’s six-phase lifecycle framework is designed to guide ethical, inclusive, and transparent development of AI systems in health care.
  • Quality Assurance Infrastructure Is Critically Needed: With no existing testing institutes for AI in health, CHAI is building a network of QA labs to evaluate tools using diverse, representative data while protecting patient privacy.
  • Transparency Empowers Providers and Patients: CHAI’s “AI Nutrition Label” includes 31 model transparency metrics and aims to support informed decision-making and foster public trust in AI.
  • Agentic AI Could Expand Access in Underserved Areas: Autonomous AI agents may help fill care gaps in resource deserts—if designed with patient values, priorities, and local context in mind.
  • Trust Hinges on Alignment with Patient Values: To build trust, AI tools must reflect what matters to patients, including their health goals, cultural beliefs, and faith. Alignment is essential for adoption and impact.

CLOSING REMARKS   

• • Omar A. Escontrías, DrPH, MPH, Senior Vice President, Equity, Research & Programs, National Health Council 

Dr. Escontrías closed the Symposium by expressing his appreciation for the patients, patient advocates, patient organizations and communities who work every day to make sure that patients are included in the pharmaceutical and medical device research and development process because it is patients who are at the center of it all.