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 Speaker Profile

Ph.D., Co-Founder & CEO, Prism AI Tx

Biography
Dr. Zviran is an experienced entrepreneur, scientist, and executive with over 20 years of experience in the defense and life science industries. Dr. Zviran co-founded C2i Genomics, where he served as both CEO and CSO. He guided the company from its beginnings as an academic spin-off to a globally recognized industry leader, culminating in a successful exit. Currently, Dr. Zviran is the co-founder and CEO of Prism AI Therapeutics, an AI-driven multi-omics CDxDx management company. Additionally, Asaf co-chair the Multi-Omics AI working group at the BLOODPAC non-profit organization.


Talk
Multi-omics AI-driven DxCDx development from small clinical cohorts
Prism AIs platform utilizes our proprietary multi-tensor spectral decomposition method to transform complex multi-omics data from early phase clinical trials into mechanistically interpretable and clinically actionable models, as well as drug efficacy and toxicity biomarkers. Our goal is to improve drug development success rates and expand the patient population that can access precision medicine.


AI and Data Sciences Showcase:
Prism AI Therapeutics

Prism AI is revolutionizing the development and management of multi-omics Diagnostic (Dx) and Companion Diagnostic (CDx) assets. Using an AI-first approach and global SaaS-like business model that can span clinical trials through commercialization, our goal is to enable the development of next-generation therapies and biomarkers.

 Session Abstract – PMWC 2026 Silicon Valley

Showcase Track S1 - March 4 11.00 A.M.-4.45 P.M.,Showcase Track S1 - March 5 9.00 A.M.-1.15 P.M.,Showcase Track S1 - March 6 10.15 A.M.-10.15 A.M.


The PMWC 2026 AI 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.

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