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How do you turn hope into action? A doctor and a public health expert answer | David Fajgenbaum and Celina de Sola

How do you hold on to hope while still being realistic about the work that needs to be done? Immunology researcher David Fajgenbaum and public health expert Celina de Sola discuss how they scaled personal missions into organizations making long-term impact on communities near and far. They explore h

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TED HostSelena De Sola GuestDavid Fagenbaum Guest

Topics Discussed

Episode Summary

Executive Summary: Selena De Sola and David Fagenbaum discuss building hope-driven systems change in public health and medicine. They connect trauma-informed care in violence-affected communities with drug repurposing for rare diseases, arguing that progress comes from humble collaboration, deep listening, AI-enabled scaling, and holding grief and hope together while continuing to act.

Main Topics: Holding hope and despair together (Priority: 5/5): Both speakers describe the emotional reality of working on life-or-death problems: success requires acknowledging grief, setbacks, and frustration without losing the drive to keep working. Drug repurposing as a life-saving strategy (Priority: 5/5): Fagenbaum explains Every Cure’s mission to identify existing medicines that can treat new diseases, using his own survival from Castleman disease as the catalyst. Trauma-informed systems change in public health (Priority: 5/5): De Sola describes Glia’s work in El Salvador and other countries to train schools, health systems, and law enforcement to better understand stress, trauma, and youth adversity. Scaling through AI and systems thinking (Priority: 4/5): Fagenbaum details how AI accelerates the search across millions of drug-disease combinations, while De Sola explains scaling by embedding training into institutions and public systems. Leadership, team-building, and communication (Priority: 4/5): Both emphasize mission-driven hiring, diverse teams, over-communication, humility, and knowing when to step back or ask for help. Vision, patience, and incremental progress (Priority: 4/5): The conversation returns repeatedly to setting a clear vision, taking one step at a time, and using small wins to sustain long-term change.

Key Arguments: Existing resources are often underused: medicines, research breadcrumbs, frontline workers, and public systems can be leveraged more effectively instead of reinventing solutions. Hope is most useful when it drives action; optimism without action can become passivity, but hope paired with work creates momentum. Systems change requires both depth and scale: close work with individuals and communities reveals real needs, while institutional partnerships allow broad impact. Humility and curiosity are essential when working across sectors because no single organization fully understands the system it is trying to change. AI can dramatically accelerate discovery by matching drugs and diseases faster than human-only approaches, but humans still must validate and implement the findings. Setbacks are part of meaningful work; organizations should learn from failure, grieve losses, and use them as fuel to work harder rather than as reasons to stop.

Data Points: Years in remission for David Fagenbaum: 11 and a half years - He has remained in remission on the repurposed medicine he tested for Castleman disease. Time since first hospitalization: 15 years - Fagenbaum notes the conversation took place on the 15-year anniversary of his first ICU hospitalization. Repurposed drugs identified: 14 drugs - Every Cure has repurposed 14 drugs for diseases they were not originally intended to treat. Patients helped: thousands of patients - Fagenbaum says thousands of patients are alive because of those repurposed drugs. AI drug-disease search space: 75 million scores - The platform evaluates every combination of 4,000 drugs and 18,000 diseases. Drug count in platform: 4,000 drugs - Used in the explanation of the AI search space for repurposing. Disease count in platform: 18,000 diseases - Used in the explanation of the AI search space for repurposing. First AI platform runtime: 100 days - The initial platform took 100 days to compute 75 million scores. Current AI platform runtime: about 17 hours - The same computation now takes roughly 17 hours. Number of people on Every Cure team: about 50 people - Fagenbaum describes the size of the nonprofit team. Number of people in Penn lab: about 20 people - He also notes the size of his University of Pennsylvania lab. Countries with national police training integration: 3 countries - De Sola says mental health training is now part of cadet training in national police in three countries. Patient response turnaround: By Thursday after a Saturday recommendation - Joseph, near hospice on Monday, improved enough to leave the ICU by Thursday after drug recommendations were made Saturday. Drug combinations recommended for Joseph: 3 drugs - Fagenbaum recommended three multiple-myeloma drugs for a POEMS syndrome patient.

Pivotal Quotes: "I feel like you can hold hope and despair at the same time, right?" — Selena De Sola: She frames the emotional challenge of sustaining difficult long-term public health work. "I'm on a mission to save and improve lives with the drugs that we already have." — David Fagenbaum: He summarizes the goal of Every Cure and the logic of drug repurposing. "The hope that drives action." — David Fagenbaum: He distinguishes productive hope from passive optimism during a discussion of setbacks.

Implications: The episode argues that high-impact health work depends on emotional resilience, cross-sector humility, and practical innovation. For listeners and institutions, the message is to use AI and systems thinking to scale proven resources while staying grounded in human need.

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