Speaker Profile
MBA, CEO & Founder, SEQSTER
Biography
Ardy Arianpour is a visionary health tech executive with 20+ years driving innovation in life sciences and digital health. In 2016, he founded SEQSTER, the leading healthcare technology company that puts the patient at the center of all their health data. SEQSTER was founded with the mission of positively impacting patient lives at scale by removing the barriers to health data access. For the first time, users create their own matched, longitudinal health data profile across all of their US-based healthcare data sources through person-centric interoperability. Ardy serves as Faculty for NextMed.Health, a Judge for the Top Tech Awards, a member of the Digital Health Advisory Board at UCSD, an Advisory Board member for Inside Precision Medicine, and a Trustee of the Fleet Science Center.
Talk
The Transformative Power of Health Data
SEQSTERs Operating System unifies fragmented health data across EHRs, labs, genomics, and wearables in real time. By creating a comprehensive, patient-centered view, SEQSTER enables researchers and healthcare organizations to generate actionable insights, accelerate clinical research, and advance precision medicine through large-scale, interoperable data connectivity.
Large-Scale Data Solutions Showcase:
SEQSTER
SEQSTER is a leading health data technology company that enables patient-centric interoperability by connecting, standardizing, and visualizing health data from any source in real time. Its Operating System empowers healthcare organizations, researchers, and patients to access complete, longitudinal health records that drive precision medicine and real-world evidence.
Session Abstract – PMWC 2026 Silicon Valley
The PMWC 2026 Large Scale Data Solutions Company Showcase will provide a 15-30 minute time slot for selected AI companies to present their latest technologies to an audience of leading investors, potential clients, and partners. We will hear from companies building technologies that expedite the pre-clinical and clinical drug discovery and development process, accelerate patient diagnosis and treatment, or develop scalable systems framework to make AI and deep/machine learning a reality.
