WIB-Seattle & GirlUP Entrepreneurs: Generative AI and Healthcare, March 27, 2024

On March 27, 2024, WIB-Seattle & GirlUP Entrepreneurs hosted the event Generative AI and Healthcare at Sage Bionetworks in Seattle. The purpose of the event was to discuss the fascinating intersection of generative AI and healthcare. In today's rapidly evolving healthcare landscape, the integration of cutting-edge technologies like generative AI holds immense potential to revolutionize patient care, diagnostics, and treatment strategies.

Margaret Kenrick, Programs Chair of WIB-Seattle, gave the opening remarks and introduced the collaborative event with GirlUp Entrepreneurs and Sage Bionetworks. Anna Hong, the CEO of GirlUp Entrepreneurs, spoke next. She gave an introduction to GirlUp Entrepreneurs, which is an organization committed to providing a nurturing space for networking, mentorship, and business growth for female entrepreneurs. Next, Anna Greenwood, Director at Sage Bionetworks, gave an introduction to Sage Bionetworks, which is a nonprofit organization in Seattle that promotes open science and patient engagement in the research process via data sharing and reuse.

From there, the moderator, Ke Du, a Senior Product Manager at Apple, introduced herself and the three speakers: Ann Novakowski, Associate Director of Governance Innovation at Sage Bionetworks; Stephanie Simmons, Director of Scientific & Regulatory Affairs at Microsoft Research Health Futures; and Jenny Cronin, Principal and Startup Incubator at AI2 Incubator. Ke asked the speakers to explain some of the major applications of generative AI in healthcare, the ethical and legal challenges of AI in healthcare, and current trends of AI models and tools in the healthcare space. After the panel, there was a Q&A session, and then the event ended with networking.

Key takeaways from the speakers included the following:

• Major applications of AI in healthcare: AI can lead to advancements in precision medicine, where treatments are tailored to a patient, like a specific mutation within their genes. In addition, AI can ease the documentation burden on physicians and clinicians with its ability to synthesize diagnostic images as well as notes from a patient visit. AI could also speed up processes such as prior authorization, which would then decrease the cost burden of the US healthcare system. Also, there is a lot of exploration involving using AI in the earliest stages of clinical research, such as drug discovery.
• Ethical/legal challenges: On the legal side, companies must be self-regulating in terms of fairness, reliability, and accountability of data sharing. Companies are sharing best practices when it comes to responsible use of AI and data sharing in order to align with international regulations. On the ethical side, biotech companies that want to innovate with health data must consider how and when a patient is willing to donate their health data for a secondary use that is beyond the primary purpose of treating their disease, such as training an AI model. The questions of "Who owns that data?" and how to restructure consent in a way that is more dynamic were also discussed, as a patient or relative of a patient may wish to donate their data after treatment has been completed. Another legal challenge that comes with sharing sensitive health data is how regulations such as HIPAA and EU GDPR mandate certain protections between patients and publicly available research and how that would apply to publicly shared and traded data sets that biotech companies may wish to train their AI models on.
• Trends in AI in healthcare: One trend is the application of real-world data to a patient, enabling an AI model to predict how a molecule may behave in an individual. Another trend is using real-world data to enable continuous learning within an AI system, which may enable more efficient treatment of patients as studies are released. A third-way trend that our panel spoke about was how AI could synthesize multi-modal information, such as radiology images and unstructured text from a physician's voice recordings, and integrate all of that information into a digestible format.

What resonated the most with attendees was the final question, "What motivates you to work on health data?" The speakers were candid about wanting to change the world and make it a better place. They spoke about how healthcare is an inspiring field to work in, yet many processes are broken. This means that there are many opportunities to improve both the system and our own health, and technology like generative AI can fill those gaps.

Submitted by Mariana Huben