GATC Health
Provider of an AI-driven multiomics simulation platform that models multi-scale human biology to support therapeutic discovery, in-silico pharmacology, clinical trial simulation, population genomic analysis, and predictive risk analytics for industry, academic, and investor stakeholders. Headquartered in Irvine, CA with additional facilities referenced in Utah, West Virginia, and Washington, D.C.
Industries
Nr. of Employees
small (1-50)
GATC Health
2030 Main Street Suite 660, Irvine, CA 92614
Products
Multiomics simulation platform
Computational platform that integrates whole-genome and other omics data with machine learning and neural-network simulations to conduct in-silico experiments for therapeutic discovery and clinical prediction.
Standardized predictive risk-reporting service
Service that produces standardized risk reports assessing likelihood of clinical-trial success and asset-level safety/efficacy risks to support capital allocation and underwriting decisions.
Multiomics simulation platform
Computational platform that integrates whole-genome and other omics data with machine learning and neural-network simulations to conduct in-silico experiments for therapeutic discovery and clinical prediction.
Standardized predictive risk-reporting service
Service that produces standardized risk reports assessing likelihood of clinical-trial success and asset-level safety/efficacy risks to support capital allocation and underwriting decisions.
Services
Computational evaluation of drug candidates to predict pharmacokinetics, toxicology, off-target effects, immune responses, and likely clinical endpoints to inform development decisions.
Processing and interpretation of large-scale genomic and other omics datasets to produce de-identified population insights and individualized predictive health reports for public-health programs.
Delivery of standardized predictive risk intelligence and scoring to de-risk development pipelines and support investor due diligence, portfolio decisions, and clinical-trial insurance underwriting.
Partnership-based projects to integrate AI analytics into partner workflows and accelerate target discovery, assay design, and therapeutic optimization.
Computational evaluation of drug candidates to predict pharmacokinetics, toxicology, off-target effects, immune responses, and likely clinical endpoints to inform development decisions.
Processing and interpretation of large-scale genomic and other omics datasets to produce de-identified population insights and individualized predictive health reports for public-health programs.
Delivery of standardized predictive risk intelligence and scoring to de-risk development pipelines and support investor due diligence, portfolio decisions, and clinical-trial insurance underwriting.
Partnership-based projects to integrate AI analytics into partner workflows and accelerate target discovery, assay design, and therapeutic optimization.
Expertise Areas
- Multiomics data integration and simulation
- AI-driven target identification and lead generation
- In-silico pharmacology (PK/ADME) and toxicology prediction
- Clinical trial simulation and predictive risk assessment
Key Technologies
- Deep learning and neural-network biological simulation
- Whole-genome and multiomics data processing
- Protein–ligand interaction prediction models
- In-silico PK/ADME/Tox modeling
News & Updates
Company co-authors a peer-reviewed paper reporting a blind-challenge demonstrating AI-based prediction of protein–small molecule interactions from chemical structures.
Feature article describing trial-outcome predictions and reporting partnerships enabling insurers to underwrite trials based on predictive risk assessments.
Partnership to analyze genomic and biological data for at least one million participants to generate individualized reports and population-level health insights.
Collaborative initiative to apply validated AI models to a large ALS dataset to identify and prioritize therapeutic targets for ALS and neurodegenerative diseases.
Agreement to apply predictive models to accelerate design and delivery optimization for circular RNA therapeutics, including delivery formulation and payload design.
Industry coverage on a partnership enabling insurers to use predictive analytics for clinical-trial underwriting and funding decisions.
Company co-authors a peer-reviewed paper reporting a blind-challenge demonstrating AI-based prediction of protein–small molecule interactions from chemical structures.
Feature article describing trial-outcome predictions and reporting partnerships enabling insurers to underwrite trials based on predictive risk assessments.
Partnership to analyze genomic and biological data for at least one million participants to generate individualized reports and population-level health insights.
Collaborative initiative to apply validated AI models to a large ALS dataset to identify and prioritize therapeutic targets for ALS and neurodegenerative diseases.
Agreement to apply predictive models to accelerate design and delivery optimization for circular RNA therapeutics, including delivery formulation and payload design.
Industry coverage on a partnership enabling insurers to use predictive analytics for clinical-trial underwriting and funding decisions.