Engineering Longevity with AI
AI-powered longevity engineering for the next generation of regenerative medicine.
COMPANY OVERVIEW
EonVita Biosciences is an AI-native biomedicine company building a dry-lab, GPU-accelerated discovery platform for longevity- and youthfulness-oriented regenerative biologics.
The platform leverages perinatal biology-derived reference datasets and AI-driven modeling to identify youthful regenerative signaling pathways associated with healthy longevity, and to computationally prioritize biologic candidates informed by youthful biological states.
EonVita is focused on computational discovery and candidate prioritization in longevity-relevant regenerative biology, with the long-term translational development of engineered biologics advancing through standard IND pathways.
EonVita is an active member of the NVIDIA Developer Program, supporting its NVIDIA-aligned approach to GPU-accelerated biomedical discovery.
TEAM STRUCTURE
EonVita’s founding team combines leadership in artificial intelligence infrastructure, regenerative biology, and venture development to build an AI-native platform for longevity discovery aligned with NVIDIA’s BioNeMo ecosystem. The team brings experience across law, finance, and platform structuring, supporting disciplined execution and governance-aligned development. Execution is intentionally sequenced. AI engineering and computational biology resources will be engaged as the platform transitions from architecture into active modeling and candidate optimization.
Sherry H. Jiang — Chief Executive Officer
AI-enabled longevity platform executive with multidisciplinary experience across law, finance, and life sciences, including an investment banking background. She also completed Stanford Online coursework in exercise physiology and healthy aging and received a verified certificate. She serves as Business Executive for EonVita, is an active member of the NVIDIA Developer Program, and is focused on building an NVIDIA-aligned platform for GPU-accelerated biomedical discovery.
Charlie Zha — Technical Advisor / Prospective Chief Technology Officer
Silicon Valley technology entrepreneur and founder of Delphix, a unicorn data infrastructure company, and architect of large-scale AI and enterprise data platforms, with experience supporting Fortune 100 organizations, including IBM. In his technical leadership role for EonVita, Charlie is helping shape a platform designed to work with large, complex biological datasets and AI-driven modeling workflows. GPU acceleration is expected to support efficient model training, scalable biological data analysis, pathway modeling, and candidate prioritization as the platform matures and data volume increases.
Scientific Leadership
EonVita is supported by senior scientific leadership, including MD-PhD expertise from top medical school environments, with experience in academic medicine, principal investigator-level research, regenerative biology, stem cell science, genetic engineering, and translational biomedical development. This background helps inform the company’s focus on youthful biological states, regenerative signaling pathways, and protein-based mechanisms relevant to longevity and tissue renewal. It also supports the biological interpretation of AI-driven discovery outputs, pathway validation strategy, and candidate prioritization within a disciplined long-term development framework.
AI LONGEVITY INFRASTRUCTURE & TECHNOLOGY ALIGNMENT
EonVita is building an AI-native longevity discovery platform architected around clearly defined GPU-accelerated deep learning workflows for high-dimensional biological systems modeling.
Core Modeling
• Graph Neural Networks (GNNs) for biological pathway inference
• Transformer-based multi-omics embeddings
• Systems-level regenerative signaling network modeling
Data & Compute Architecture
• Integration of genomic, proteomic, and metabolic datasets
• PyTorch-based model development with CUDA-enabled GPU acceleration
• Scalable distributed GPU training environments
Compute Scaling Roadmap
Phase 1 – Prototype biological modeling
Phase 2 – GPU-accelerated multi-omics optimization
Phase 3 – Distributed multi-GPU systems-level scaling
EonVita’s computational architecture is intentionally aligned with NVIDIA’s accelerated computing ecosystem to support scalable biological modeling, performance optimization, and long-term platform growth.