Yatiri Bio


Yatiri Bio is revolutionizing drug discovery by integrating proteomics, deep learning, and patient data to improve clinical development and patient outcomes. The company focuses on developing novel tools for analyzing proteins as functional drivers of disease, facilitating the discovery of therapeutic signatures, and predicting patient outcomes to match individualized therapeutics, aiming to transform current medical practices.

Industries

biotechnology
medical
pharmaceutical

Nr. of Employees

small (1-50)

Yatiri Bio

San Diego, California, United States, North America


Products

ProteoModelsTM

A portfolio of cellular models backed by clinical proteome data, used for patient selection, combinational therapies, drug repurposing, identifying resistance mechanisms, and drug discovery with biomarkers.

ProteoBrowserTM

An interactive platform integrating proteomics data, computational biology, and machine learning for drug discovery, providing access to proprietary and public proteomic data.

PTM Enrichment and Analysis

A service offering tailored post-translational modification enrichment and analysis to discover signaling pathways, including a pipeline optimized for phosphoproteomics.

Efficacy Models

A collection of tailored models for identifying therapeutic indications, selecting ideal patients for clinical trials, and exploring combination therapies with deep pathway analysis and biomarker identification.


Services

Global proteomic profiling service

Unbiased quantitative proteomic analysis via high-resolution mass spectrometry for cell lines, organoids, tissues, and clinical samples with optimized processing protocols.

PTM and phosphoproteomics analysis

Tailored enrichment and analytical workflows to detect and quantify post-translational modifications and signaling events relevant to disease biology.

Proteomic data analysis and biomarker discovery

Integrated bioinformatics analysis using a proteomic database to identify biomarker signatures, mechanisms of resistance, and markers for patient selection.

Deep learning modeling for clinical outcome prediction

Development and application of deep learning models that map proteomic readouts to predicted patient outcomes to inform clinical development and trial design.

Interactive proteomics data portal

Web-based portal for interrogation of experimental proteomic data in the context of internal and public databases to facilitate data exploration and decision making.

Expertise Areas

  • Mass spectrometry–based proteomics
  • Phosphoproteomics and PTM analysis
  • Proteomic biomarker discovery
  • Bioinformatics for proteomics
  • Show More (4)

Key Technologies

  • High-resolution mass spectrometry
  • Phosphoproteomics
  • Post-translational modification enrichment
  • Proteomic databases
  • Show More (3)

Similar organizations

Browse all ORGANIZATIONS

JOIN OUR MAILING LIST

Stay Connected with MTEC

Keep up with active and upcoming solicitations, MTEC news and other valuable information.