Applied AI Summit Healthcare
Free online conference | April 14-15, 2026AI Engine to Maximize Commercial Reach
In the modern pharmaceutical landscape, the greatest barrier to maximizing commercial reach is often the “invisible patient”—individuals suffering from conditions who remain undiagnosed or misdiagnosed. This session introduces a novel technical framework leveraging Artificial Intelligence to bridge the gap between clinical efficacy and patient access. We present a dual-module system: first, utilizing predictive machine learning on Real-World Data (RWD)—including claims and referral patterns—to identify high-probability patient signals; and second, deploying Generative AI (LLMs) to synthesize these complex insights into actionable, personalized engagement tools for field teams.
By automating the translation of raw data into commercial intelligence, this approach moves beyond traditional “share of voice” marketing toward “precision patient finding.” Attendees will learn how to architect scalable GenAI solutions that navigate regulatory constraints while unlocking significant new market opportunities, ultimately ensuring that life-changing therapies reach the patients who need them most.
About the speaker
Shihan He
Machine Learning Engineer at Novo Nordisk Inc.
Shihan He is a dynamic Machine Learning Engineer and Team Lead within the AI Engineering and GenAI division at Novo Nordisk. Situated at the intersection of advanced analytics and commercial strategy, she is dedicated to leveraging Artificial Intelligence to maximize patient reach and optimize the commercialization of life-changing therapies. Shihan’s work focuses on deploying Generative AI solutions that enhance commercial operations and decision-making. By applying Large Language Models (LLMs) to complex market data, she helps bridge the gap between technical innovation and patient access, ensuring that vital treatments reach the people who need them most. Her expertise in Operations Research allows her to design systems that not only improve efficiency but also drive smarter, data-backed commercial execution. A recognized voice in the industry, Shihan actively shares her insights on the future of AI in pharma. She has served as a speaker at prominent events such as the BioTechX USA conference in Philadelphia and the Re-Work AI in Healthcare & Pharma Summit in Boston, advocating for the responsible use of AI to transform healthcare delivery.