drug discovery

with the next generation of
patient selection
Novel therapeutic targets
unlocking unique biology
and deep learning

driving a new era of
clinical development

Building Revolutionary Tools

Over the last 200 hundred years of human research, it has become clearly evident that proteins are the drivers of biology and disease. Yet, the focus of most pharmaceutical companies is still reliant on the acquisition of genetic data to help discover new medical advances. This current approach is costly ($3B), requires a long period of time (~12 years for a drug to come to market), and contains many translational failures (only 5% of therapeutics entering clinical trials achieve FDA approval). The recent technological advances in the quantitation of the thousands of proteins expressed in a cell (proteomics) have opened broad new horizons for drug discovery.
Yatiri Bio is here to change this narrative, re-envisioning the pharmaceutical industry's current drug discovery process by integrating patient data sets with testable empirical models to guide patient selection and clinical development.

Bridging The Gap

Yatiri Bio is dedicated to integrating and maximizing proteomic knowledge to drive improved patient outcomes through a streamlined research and development pathway. First, we develop novel proteomics and bioinformatics tools to analyze proteins as the functional drivers of disease. This facilitates the discovery of robust therapeutic signatures, thereby improving patient stratification and selection. The second part of our approach exploits deep learning algorithms to position empirical models withing a learned space to efficiently predict patient outcomes. These clinically relevant models can be used to test novel therapies with greater precision, thereby eliminating inefficiencies while creating a dynamic path toward more successful patient outcomes.
Our overarching goal is to match a patient’s proteomic readout to individualized therapeutics at the biochemical level, which will revolutionize the current practice of medicine.