Viatris; Founder, AI4Purpose

Kelly H. Zou

Academic and industry research play a crucial role in developing commercial health technologies. Health technologies, such as AI, encompass digital health solutions, big data analytics and predictive algorithms to address healthcare needs, such as patient care management and data protection. Entrepreneurs transitioning to a startup or tech world must recognize that the landscape differs significantly from theoretical research. Taking an AI algorithm developed in a laboratory and turning it into a commercial product involves technical proficiency but demands insights into funding, business strategy and end-users' needs. They must learn to balance research with entrepreneurship, making strategic decisions that allow their innovations to thrive in real-world environments. Moreover, two important considerations, i.e., funding and technology transfers, are critical for short- and long-term successes.

Real-world data (RWD) and real-world evidence (RWE) illustrate the importance of interdisciplinary learning. Many students have launched successful startups based on research projects by leveraging engineering, computer science and public health insights. This approach demonstrates how innovation can be fostered within academic institutions while addressing healthcare challenges. By nurturing entrepreneurial thinking early, universities prepare students for diverse career opportunities and contribute to advancements in AI and related fields.

Interdisciplinary collaboration is another key factor in successfully developing and implementing health technologies. Healthcare challenges are complex, requiring expertise from multiple fields. Engineers, clinicians, data scientists and policymakers must work together to create holistic solutions. Innovations seamlessly integrated into clinical workflows and policy decisions tend to be more successful and effective. Developing a digital health platform for chronic disease management is a compelling example of interdisciplinary collaboration. Software developers, healthcare providers and patient advocates worked together to create a user-centric system to improve patient outcomes while reducing healthcare costs. Such projects demonstrate how combining diverse expertise leads to more comprehensive and impactful innovations.

However, navigating regulatory frameworks is nontrivial and requires thorough planning. Furthermore, cultural context, policy frameworks and industry standards influence the implementation of new technologies. As AI-trained graduates increasingly enter the private industry sector, academic programs must evolve to align with current trends, ensuring that students receive specialized training that prepares them for the workforce. Thus, entrepreneurs must engage legal experts early in their development process to establish robust data governance protocols. Balancing innovation with accountability ensures that new technologies uphold ethical standards while meeting industry requirements. Organizations that successfully manage compliance demonstrate their commitment to protecting sensitive health data, which is critical in gaining user trust and widespread adoption.

Furthermore, regulatory compliance plays a significant role in developing and commercializing creative solutions. The healthcare industry is highly regulated to protect patient data and ensure ethical practices. Regulations such as the Health Insurance Portability and Accountability Act (HIPAA) in the United States and the General Data Protection Regulation (GDPR) in the European Union establish strict data privacy and security guidelines. While compliance presents challenges for entrepreneurs, it is a necessary safeguard for maintaining patient trust.

Technological advancements have a tangible impact on healthcare, enhancing diagnostics, improving care coordination and empowering patients. AI-driven tools assist clinicians in making faster and more accurate diagnoses, while digital health platforms provide seamless communication between patients and providers. As healthcare systems adopt more technology-driven solutions, these innovations will continue to evolve, offering greater efficiency and better health outcomes. Academia is an innovation hub where groundbreaking healthcare solutions are created, but transitioning research into practical applications requires resilience, adaptability and strategic planning. Researchers moving into the startup world must consider scalability, user adoption, and competition. Success depends on business acumen, understanding stakeholder needs and navigating regulatory requirements. Mentorship, interdisciplinary partnerships and continuous feedback help refine innovations. Research training provides a strong foundation for problem-solving, an invaluable skill in both academic and business settings. Academics pursuing commercial ventures must learn to balance their efforts across research, business development and teaching responsibilities. Time management and delegation help streamline operations and allow entrepreneurs to focus on driving meaningful innovation.

In summary, bridging academia and commercialization is essential for driving health tech and AI to shape the future of healthcare landscapes. Innovators can create meaningful advancements that improve health outcomes by encouraging and fostering interdisciplinary collaboration, incorporating business acumen into academic training and addressing regulatory challenges. The next generation of AI-savvy professionals will play a crucial role in shaping the future of healthcare technologies. Aspiring entrepreneurs must develop skills beyond technical expertise, including securing funding, managing multiple responsibilities and building strong professional networks. Entrepreneurial journeys often involve overcoming obstacles and learning to make strategic business decisions while maintaining research integrity. Effective stakeholder management, regulatory navigation and scaling operations are essential to successfully transitioning from academia to industry.

Acknowledgment: the panelists were John J. Doyle, Fortrea (Former Employee), Nicolle M. Gatto, Aetion, Rich E. Gliklich, MD, OM1, Ilker Hacihaliloglu, CTO, PONS Tech, Stan Kachnowski, HITLAB, and Paul A. Keown, Syreon Corporation/Institute.

Disclaimer: the views and opinions were the panelists’ own and may not necessarily reflect their respective companies’.