Digital Healthcare [TWIN]
Bean is building a complete molecular-level digital twin of the human body—blood, tissues, and organs—to understand, slow, and ultimately reverse aging.
The North Star
Aging is not inevitable—it is a biological process driven by molecular damage, protein misfolding, and cellular dysfunction. By building precise digital replicas of every biological system in the body, we can model how aging unfolds and design interventions to stop it.
Bean's north star is a complete, personalized digital twin of the human body—one that captures every protein, cell type, tissue, and organ at molecular resolution.
The Problem
We cannot treat what we cannot model. Current medicine operates on population averages—not on the individual molecular biology of each person.
Average cost to bring a drug to market
Of drugs fail in clinical trials
Approved therapies that reverse aging
What We're Building
A full-body digital twin, built from the ground up—one biological system at a time.
Blood Digital Twin
Molecular-level models of every protein in human blood. Built from individual patient sequences using AI-powered structure prediction (AlphaFold-based). The foundation for understanding systemic aging markers.
Tissues & Organs
Extending beyond blood to model soft tissues, connective tissue, and major organs. Each tissue type adds a new layer of biological resolution to the twin.
Neural Systems
Modeling the nervous system and brain at the cellular level—enabling digital representations of cognitive aging, psychiatric biomarkers, and neuroprotective interventions.
Complete Human Twin
A unified, personalized model of every biological system—the foundation for simulating aging trajectories, testing anti-aging interventions in silico, and personalizing longevity medicine.
How It Works
From a patient's protein sequence to a navigable 3D digital twin in three steps.
Input Sequence
Submit a protein sequence in FASTA format—sourced from patient samples or public databases like UniProt.
Structure Prediction
Our AlphaFold-based pipeline predicts the 3D molecular structure of the protein with atomic precision.
Digital Twin
The predicted structure is integrated into an interactive digital twin—a navigable biological model of the individual.
The Team
Deep expertise across software engineering, AI, neuroscience, and clinical medicine.
Dinesh Appavoo
CEO & Co-Founder
B.Tech, MS, MS — Computer Science
Built and scaled products at Affirm, Twitter, and AWS (ALB/ELB serving millions of machines). Previously founded Labineer, a healthcare marketplace, and Hypersona Inc., a rocket propulsion company.
Olivia Levine
Advisor
MD, PhD — Neuroscience (Weill Cornell)
Psychiatry Resident at Maimonides Medical Center. PhD research on neural circuits and addiction. Published in Nature Communications. NIDA grant recipient.
Interested in Bean?
We're at the early stage and open to conversations with investors, researchers, and collaborators who share our mission to defeat aging.