Promise Bio raises $8.3 million in Seed funding for its precision medicine tool for diseases
Promise Bio raises $8.3 million in Seed funding for its precision medicine tool for diseases
The Israeli startup's computational platform uses epiproteomics and AI to predict patient treatment responses and support drug research and development.
Promise Bio, a startup working toward immune-mediated disease treatment with advanced precision medicine solutions, has announced its emergence from stealth with a Seed investment of $8.3 million. The round was led by Awz Ventures with funding via AION Lab’s venture seeding track from AstraZeneca and Pfizer as well as a grant from the Israel Innovation Authority.
The funding will accelerate the development of its computational platform, which uses epiproteomics and AI to predict patient treatment responses and support drug research and development.
"Current biological treatments for autoimmune diseases don’t work in all patients, with only 30-40% of patients achieving significant remission," said Ronel Veksler, Co-founder and CEO. "At Promise Bio, our mission is to eliminate the trial-and-error approach by introducing tools for data-driven decisions. The key to addressing this challenge lies in focusing on the right biological data—proteins, the building blocks of our body. It's not just about protein levels but understanding the changes they undergo after formation. The PROMISE (Protein Modification Integrated Search Engine) platform does exactly that, enabling us to get closer to bringing precision medicine to diseases that currently lack effective tools."
Promise Bio’s platform is rooted in years of foundational research conducted by Dr. Assaf Kacen, Co-Founder & CTO of Promise Bio, in the lab of Prof. Yifat Merbl, Scientific Co-Founder of the company, at the Weizmann Institute of Science. The research into protein modifications and immune response laid the foundation for developing the company’s computational platform.
The system enables broad-scale profiling of dozens of post-translational modifications (PTMs) from mass-spectrometry data without needing customized chemical enrichment or additional lab procedures.
"Determining the change in the protein level or relying on just blood count caused by a complex immune response is like looking at a black-and-white TV screen with poor resolution," added Dr. Kacen. "Our platform extracts modifications that occur to the proteins resulting from the disease; those specific changes inform us about aberrations in protein function or regulation. Interpreting it with machine learning approaches is like watching a colored TV with an unparalleled high-resolution view of the underlying biology."
