
About
Drug development has a gambling problem

Developing a single new drug costs $2.6 billion and takes 12.5 years. Almost all of the drugs that do make it to clinical trials fail, even after rigorous animal testing. The odds of clinical trial success are the equivalent of betting on a single number in roulette, with a 97.3% chance of losing. But despite this colossal failure rate, pharma hasn’t changed its process for creating and testing drugs in 90 years. Pharma keeps placing the same bad bet on animal models, and patients are left to pay the price.
We founded Parallel Bio to solve the real reason why drugs fail.
We founded Parallel Bio to solve the real reason why drugs fail.
Our first achievement was the development of the world’s first scalable human immune organoid, designed to capture the human biology that animal models miss. Since then, we’ve reimagined the entire drug discovery process, incorporating cutting edge biological and computational tools to generate unprecedented insights into human health and disease. Our approach allows us to predict how therapies may perform across diverse patient populations, enabling earlier and more reliable decisions than any existing preclinical model.
Our biobank features over 170 donors spanning different ages, sexes, ethnicities, disease states, and genetic backgrounds. With more population diversity than many clinical trials achieve, we generate meaningful data without putting a single patient at risk. When we collect data, we're not asking, "Does this drug work in genetically identical male mice?" We're asking, "How does this drug perform across the actual human population?"
Our biobank features over 170 donors spanning different ages, sexes, ethnicities, disease states, and genetic backgrounds. With more population diversity than many clinical trials achieve, we generate meaningful data without putting a single patient at risk. When we collect data, we're not asking, "Does this drug work in genetically identical male mice?" We're asking, "How does this drug perform across the actual human population?"
By shifting drug development from guesswork to human-first prediction, we aim to dramatically reduce clinical failures and bring safer, more effective therapies to patients in need. Our new model of pharma will generate medicines for patients 10x faster at a thousandth of the cost, unlock the potential for personalized medicine in ways not previously possible, and generate compounding data rich for modeling and learning in this new era of computational intelligence.
Join us as we push the boundaries of what's possible.
Robert & Juliana
Co-Founders of Parallel Bio
Co-Founders of Parallel Bio
Meet the team
Bringing together immunotherapy, data science, bioengineering, and drug discovery experts.

Kelly Volk
Associate Scientist

Belinda Chin
Staff Software Engineer

Michael Paolucci
Lead Principal Automation Engineer

Sophia Pete
Associate Scientist

Shona Cronin
Scientist

Amr Aly
Senior Software Engineer
Join our team!
Our Advisors

Darrell Irvine
Bioengineering
Professor and Vice-Chair, Department of Immunology & Microbiology, Scripps Research

Nima Aghaeepour
Data Science
Vice Chair of Research, Professor of Biological Data Science, Stanford

Shane Crotty
Immunology
Professor and CSO, La Jolla Institute for Allergy and Immunology

Andre Esteva
AI + Data
CEO and Co-Founder of ArteraAI, ex-Head of Medical AI at Salesforce

Ron Philip
Strategy
Former CEO of Orbital Therapeutics, former CEO of Spark Therapeutics
Our Investors


































