Syntegra Synthetic Data

by Syntegra  · Based in United States → — Democratizing data access to accelerate innovation for improved patient care and outcomes.
Laboratory Medicine Pathology Radiology
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Not available (company out of business)
Regulatory Status Disclosed

Overview

Syntegra was a company that leveraged generative AI to create high-fidelity, privacy-preserved synthetic healthcare data. Their proprietary algorithm, known as the Syntegra Medical Mind, was designed to learn the underlying statistical patterns of real patient data to generate ‘realistic but not real’ datasets. This technology aimed to unlock the promise of healthcare data by increasing its utility while fully protecting patient privacy, going beyond traditional HIPAA and GDPR compliance standards.

The platform enabled organizations to access and utilize patient-level data for various purposes without the complexities and privacy concerns associated with real patient data. Syntegra offered services such as data licensing, custom generation, and augmentation, which included expanding population sizes for rare cohorts, balancing biased populations, and imputing missing data.

Note: According to PitchBook, Syntegra (the synthetic healthcare data platform operator) was marked as ‘Out of Business’ as of October 23, 2023.

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Key Features

  • Generative AI technology (Syntegra Medical Mind)
  • High-fidelity synthetic datasets
  • Privacy-preserving (no real patient information)
  • Statistically representative of real data
  • Captures rare cohorts and outliers
  • Supports large and complex datasets (e.g., 20M+ patient records, longitudinal data)
  • API for data licensing and delivery
  • Data augmentation capabilities (expand cohorts, balance bias, impute missingness)

Use Cases

  • AI/ML model training and testing
  • Product development and testing (e.g., digital health, interoperability infrastructure)
  • Real-world evidence (RWE) and clinical trial design
  • Academic research and education
  • Secure data sharing and collaboration
  • Improving disease prediction and detection

What Physicians Need to Know

Healthcare API Support (FHIR/HL7)
Syntegra's synthetic EHR data is available in FHIR USCDI format, covering labs, medications, vitals, encounters, and patient demographics. The platform can work with semi-structured data formats like HL7 FHIR resources, JSON clinical messages, and XML-formatted EHR exports.
HIPAA-Compliant Infrastructure
Syntegra's synthetic data is designed to be privacy-preserving, surpassing HIPAA and GDPR compliance by generating 'realistic but not real' datasets that contain no actual patient information. Independent validation studies have shown its synthetic data to have statistically indistinguishable properties from source HIPAA-protected data.
Clinical NLP Capabilities
The Syntegra Medical Mind, a proprietary machine learning algorithm, leverages transformer-based language models (similar to GPT-2 and GPT-3) to learn the underlying statistical patterns and 'language' of patients' clinical trajectories from real healthcare data (EHR, claims, genomics). This enables the generation of new synthetic patient records that preserve complex clinical patterns.
De-Identification Tools
Syntegra's approach generates entirely new synthetic datasets, which inherently contain no real patient information, thus eliminating re-identification risk. This is distinct from traditional de-identification methods that modify existing real data and may still carry residual risks.
Medical Terminology Support
The platform preserves clinical patterns and captures detailed temporal sequences of medical events, including diagnoses, lab results (with timing), medications (with timing and dosing), vital signs, patient location, and physician roles. It can handle all types of structured healthcare data, maintaining statistical fidelity even for rare cohorts and outliers.
Sandbox/Testing Environment
Syntegra's synthetic data is ideal for building and testing healthcare AI applications in non-HIPAA environments, reducing development costs and risks associated with real patient data. It supports software development, integration testing, and regulatory sandbox environments.
SDK Languages
Syntegra utilizes the AWS Python SDK (boto3) for scaling its synthetic data engine, indicating Python as a supported language for integration.
Rate Limits & Pricing
Syntegra offers data licensing on a monthly basis via API or direct delivery, with custom generation typically available through annual or monthly licenses. Augmentation services are charged at a flat rate. The cost of accessing synthetic data is significantly lower than real-world data. Enterprise licensing models for unlimited synthetic data generation on a subscription basis are also available.
Certification Program
Syntegra's synthetic data undergoes rigorous privacy evaluation and statistical fidelity testing, with documented metrics to demonstrate performance. While not explicitly a user-facing certification program, the broader industry is moving towards synthetic data certification to prove synthetic origin and integrity for AI governance and compliance.
Physician Tip

Syntegra's synthetic data offers a powerful tool for physicians and researchers to explore complex disease trajectories, understand diverse patient responses to treatments, and analyze rare disorders without compromising patient privacy. It can be invaluable for training AI models for diagnostics and predictive analytics, developing equitable treatment plans by addressing data bias, and facilitating research that would otherwise be hampered by data access restrictions. The ability to generate large, representative datasets, including augmentation for rare cohorts or missing values, can significantly accelerate medical understanding and innovation.

Syntegra's synthetic data can be integrated into various healthcare ecosystems, including EHR systems (via FHIR USCDI and other structured formats), and can fuel digital health platforms, life science research, and health analytics tools. Partnerships, such as with Datavant, enable seamless and compliant exchange of privacy-preserved synthetic healthcare data. The API-first approach and support for various data formats (.bin, .json, .xml, .csv, .xls, .sql, .txt) facilitate integration into existing data pipelines and AI/ML development workflows.

Details

Category Developer Tools & APIs, Legal, Compliance & Security
Pricing Not available (company out of business) — Not Available (Company Out of Business)
DeploymentSaaS layer, Web-Based
Compliance
BAA AvailableUnknown AI-estimated
HIPAA CompliantUnknown AI-estimated
FDA Status No AI-estimated — Not applicable for a synthetic data generation platform.
Integrations
EHR Not specified
Specialties Laboratory Medicine, Pathology, Radiology

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Press & Coverage

PR Newswire
Syntegra Pushes the Boundaries of Generative AI in Healthcare with Recent Tech Updates
Syntegra launched Syntegra Medical Mind 2.0, an advancement in generative AI for high-fidelity, privacy-guaranteed synthetic healthcare data, enabling easier and safer data sharing and accelerated AI/ML model development. The update allows training on datasets with over 20 million patient records and supports long sequence lengths for patient care trajectories.
2022-11
GlobeNewswire
Syntegra and Datavant Partner to Enable the Exchange of Synthetic Data Across the Healthcare System
Syntegra and Datavant announced a partnership to integrate Syntegra's synthetic data capabilities into the Datavant Switchboard, allowing for the secure and compliant exchange of privacy-preserved synthetic healthcare data. This collaboration aims to accelerate healthcare innovation by providing enhanced privacy and data security.
2022-12
PR Newswire
Syntegra Partners with InterGen Data to Provide a Safe Way of Leveraging Healthcare Records to Predict Life Events
Syntegra partnered with InterGen Data to use synthetic data for predicting life events, enabling financial services, insurance, and home healthcare companies to leverage healthcare records in a privacy-guaranteed manner. This aims to improve individuals' planning and well-being by providing secure access to patient-level healthcare information.
2022-10
PR Newswire
Syntegra and the Institute for Health Metrics Expand Strategic Partnership to Bring Privacy-Guaranteed Healthcare Data to Life Sciences
Syntegra and the Institute for Health Metrics (IHM) expanded their partnership to provide life sciences companies with easier and faster access to millions of privacy-guaranteed electronic health records. This collaboration combines Syntegra's synthetic data engine with IHM's data repository to enable innovation without privacy risks.
2022-10
Indian Pharma Post
Syntegra partners with TMA Precision to reduce the diagnostic odyssey for rare disease with synthetic data-enabled tools
Syntegra announced a partnership with TMA Precision Health to utilize synthetic data for improving the diagnosis of rare diseases globally. TMA will leverage Syntegra's synthetic data engine to accelerate the development of predictive diagnostic algorithms, aiming to reduce the diagnostic odyssey for patients.
2022-06
Hospitalogy
Syntegra and Synthetic Data: Solving Healthcare's Data Problem
This article discusses how Syntegra's synthetic data addresses the challenges of accessing high-fidelity healthcare data due to privacy concerns and regulatory roadblocks. It highlights use cases in digital health, life sciences, and academic research, emphasizing the potential to accelerate innovation and improve patient care.
2022-09
PR Newswire
Syntegra Partnering with National Institutes of Health (NIH) and the Bill and Melinda Gates Foundation to Democratize Access to the Largest Set of COVID-19 Patient Records
Syntegra collaborated with the NIH and the Bill and Melinda Gates Foundation to validate its AI-enabled synthetic data technology for COVID-19 research. This initiative aims to provide less restricted access to a vast repository of patient-level COVID-19 electronic medical records, accelerating insights and drug development.
2021-01
Frontiers in Artificial Intelligence (via PMC)
Virtual Cohorts and Synthetic Data in Dementia: An Illustration of Their Potential to Advance Research
This peer-reviewed article demonstrates the use of Syntegra's synthetic data engine to create virtual cohorts from the EPAD V1500 dataset, preserving statistical properties while ensuring privacy. The study validates the fidelity of the synthetic data, showcasing its potential to advance dementia research.
2021-04

Videos

Product demos, reviews, and walkthroughs for Syntegra Synthetic Data.

View all on YouTube

Frequently Asked Questions

Syntegra Synthetic Data is artificially generated patient data that mimics the statistical properties and patterns of real patient information, including Electronic Health Records (EHR), claims, and genomics. It's used in healthcare AI to train diagnostic models, test software, conduct research, and for educational purposes without compromising actual patient privacy.
Syntegra's synthetic data is designed to be privacy-guaranteed because it contains no actual patient information, making it inherently compliant with regulations like HIPAA and GDPR. Since it's entirely computationally generated and cannot be traced back to real individuals, it significantly reduces the risk of re-identification.
Physicians and healthcare organizations can benefit from enhanced data accessibility for research, faster AI model development, and improved clinical decision-making without the traditional privacy hurdles. It allows for the exploration of disease patterns, training of AI systems, and testing of new treatments using realistic data that is readily available and scalable.
While highly useful, synthetic data may sometimes sacrifice a degree of realism or clinical utility compared to original patient data. It's crucial to rigorously validate synthetic data to ensure it accurately reflects the real-world distributions and relationships for specific use cases.
Several other companies offer synthetic data solutions, including MDClone, Gretel, Hazy, Mostly AI, Tonic.ai, and Syntho. Additionally, open-source tools like Synthea can generate synthetic patient data, providing various options depending on specific data types, privacy requirements, and computational resources.
Syntegra generally offers flexible pricing through a Software-as-a-Service (SaaS) model, with options for monthly or yearly licenses to access its API. This approach aims to be more cost-effective and adaptable compared to the often prohibitive costs associated with traditional real-world data vendors.

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Suggest an Edit → | Last Verified: 2026-05-12 | First Added: 2026-05-12
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