Yatiri Bio Inc.  announced it has received a grant from the Gates Foundation to launch a one-year project, Proteomics Interoperability, aimed at improving how large-scale proteomics data can be integrated and applied to global health challenges.

Proteomics, the large-scale study of proteins, has emerged as a cornerstone of modern drug discovery, driving the search for new drug targets, early detection biomarkers, and measures of treatment efficacy. However, the field faces a critical challenge: data is generated using multiple, distinct technologies, each with strengths and limitations. Yatiri Bio aims to overcome this challenge with this project, which will develop advanced machine learning models to bridge these technologies, enabling the combination of diverse data types into a unified, interpretable framework.

The project will focus on HPV-related cervical cancer, a significant health priority for the Foundation given its disproportionate impact on women in low- and middle-income countries. Yatiri Bio will analyze matched tumor and adjacent non-cancerous tissues using three complementary approaches: unbiased proteomics (Yatiri Bio), aptamer-based proteomics (Somalogic), and antibody-based proteomics (Olink). By integrating these datasets, the company aims to demonstrate how proteomics interoperability can reveal more reliable disease signatures and accelerate the development of precision medicine.

“Our mission is to make advanced proteomics insights broadly accessible and clinically meaningful,” said Pilgrim Jackson, CEO of Yatiri Bio. “With the support from the Foundation, we can facilitate the integration of proteomics datasets across modalities to inform drug discovery and early detection strategies for diseases like HPV-related cervical cancer, while also creating a scalable model that can be applied globally.”

Yatiri Bio will develop and optimize a deep neural network architecture to integrate proteomics data across platforms. In addition to addressing the technical challenge of data harmonization, Yatiri Bio will generate a reference dataset and methods that can be shared with the scientific community, strengthening the field’s ability to apply proteomics at scale.