--- title: "Synthetic Data, Definition | MedTech Terms" description: "Artificially generated data used to augment training, validation, or stress-testing of medical AI. Plain-English Software & AI definition for MedTech teams, wit" lang: en json-ld: | { "@context": "https://schema.org", "@graph": [ { "@type": "DefinedTerm", "@id": "https://medtechterms.com/terms/synthetic-data#term", "name": "Synthetic Data", "description": "Synthetic data is generated by simulators, generative models, or rule-based systems. 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However, if the synthetic data generation process is flawed, it could inadvertently introduce new vulnerabilities or fail to mimic real attack vector complexities." } } ] } ] } --- [ MedTech Terms The authoritative reference ](/) Browse Learn [Latest](/latest) About 1. [Home](/) 2. / 3. [Terms](/terms) 4. / 5. [Software & AI](/terms?cat=Software%20%26%20AI) 6. / 7. Synthetic Data [All terms](/terms) Software & AI [AI / ML in Devices](/ecosystems/ai-ml)[Software Lifecycle](/ecosystems/software-lifecycle) # Synthetic Data Artificially generated data used to augment training, validation, or stress-testing of medical AI. Reviewed by [Christian Espinosa, Founder, Blue Goat Cyber](/authors/christian-espinosa) Last reviewed May 5, 2026 ## Definition Synthetic data is generated by simulators, generative models, or rule-based systems. Used to balance underrepresented subgroups, model rare events, or substitute for sensitive data - but introduces realism, leakage, and bias-amplification risks. What the regulation says Regulators recognize the utility of synthetic data for MedTech, particularly in AI/ML model development and validation as outlined in FDA guidance documents like "Content of Premarket Submissions for Device Software Functions" and "Marketing Submission Recommendations for Predicate Devices Used in Artificial Intelligence and Machine Learning-Enabled Medical Devices." However, they emphasize the need for rigorous validation to ensure the synthetic data accurately reflects real-world clinical data distributions and characteristics, without introducing new risks such as bias or reduced generalizability. The [IMDRF](/terms/imdrf) also addresses data quality considerations, which would extend to synthetic data, underscoring the importance of its suitability for regulatory decision-making. ## What this means in practice FDA has explicitly noted both the promise and the limits of synthetic data for training and validation; transparent reporting is expected. ## Examples - Synthetic data is used to train an AI algorithm for detecting rare disease anomalies in medical images, where real patient data is scarce. - A manufacturer employs synthetic patient records to test the cybersecurity resilience of a new medical device software without compromising actual patient privacy. - Synthetic control arms are sometimes explored in clinical studies to reduce the number of patients exposed to a placebo, though this requires strong statistical justification and regulatory acceptance. Common pitfalls - • A common pitfall is generating synthetic data that fails to capture the true underlying statistical properties or rare events accurately, leading to models that perform poorly in real-world scenarios. - • Another mistake is using synthetic data without sufficient transparency regarding its generation methods, assumptions, and validation, which can hinder regulatory review. - • Failing to address potential biases amplified during synthetic data generation is a significant pitfall, as it can perpetuate or exacerbate inequities in AI/ML-enabled medical devices. - • Over-reliance on synthetic data without subsequent validation against real-world data can lead to a false sense of security regarding model performance and safety. - • A pitfall is not adequately assessing the impact of synthetic data on the overall risk management strategy of a medical device, especially regarding safety and effectiveness. ## Frequently asked questions What is the primary regulatory concern with synthetic data? The primary concern is ensuring that synthetic data maintains the validity, representativeness, and integrity of [real-world data](/terms/rwd) without introducing new biases, vulnerabilities, or misrepresentations that could affect the safety and effectiveness of a medical device. Can synthetic data be used for clinical trial endpoints? How does synthetic data impact cybersecurity? ## Related terms Grouped by theme ### Editor's picks · Hand-selected related concepts [ Software & AI Algorithmic Bias and Fairness Systematic differences in model performance across demographic or clinical subgroups. ](/terms/ai-bias-fairness)[ Software & AI Data Governance (AI/ML) Policies, controls, and documentation for the data used to train, tune, and validate medical AI models. ](/terms/data-governance) ### More in Software & AI · Same category [ Software & AI AAMI TIR45(TIR45) AAMI Technical Information Report providing guidance on applying Agile software development practices within an IEC 62304-compliant medical device software lifecycle. ](/terms/aami-tir45)[ Software & AI Adversarial Robustness Resilience of an ML model to inputs deliberately crafted to cause misclassification. ](/terms/adversarial-robustness)[ Software & AI AI/ML-Enabled Medical Device Medical device that uses artificial intelligence or machine learning to perform its intended use. ](/terms/ai-ml-device)[ Software & AI Algorithm Change Protocol(ACP) The detailed procedural section of a PCCP that specifies how planned modifications to an AI/ML model will be developed, validated, and implemented. ](/terms/algorithm-change-protocol) Cited by Where this term appears across MedTech Terms. Ecosystems (2) - [AI / ML in Devices](/ecosystems/ai-ml) - [Software Lifecycle](/ecosystems/software-lifecycle) ## Primary references 3 sources Link health: 3 verified · last checked 2026-06-20 FDA· 1 IMDRF· 1 MDCG· 1 1. [1 FDA Synthetic Data Discussion Verified FDA · fda.gov ](https://www.fda.gov/medical-devices/software-medical-device-samd/artificial-intelligence-and-machine-learning-software-medical-device) 2. [2 IMDRF - Software as a Medical Device Verified IMDRF · imdrf.org ](https://www.imdrf.org/working-groups/software-medical-device-samd) 3. [3 MDCG Software Guidance Verified MDCG · health.ec.europa.eu ](https://health.ec.europa.eu/medical-devices-sector/new-regulations/guidance-mdcg-endorsed-documents-and-other-guidance_en) Inline markers like \[1\] jump to the matching reference above. Sponsor note ### Building software-as-a-medical-device? We help SaMD and AI/ML device teams meet IEC 62304 and the FDA's evolving expectations for software cybersecurity. [Book a 30-minute discovery session](https://go.bluegoatcyber.com/meetings/blue-goat-cyber/discovery-session) - No obligation - Expert-led from minute one - NDA available on request MedTech Terms is a community resource sponsored by [Blue Goat Cyber](https://bluegoatcyber.com). Definitions are independent of any vendor. On this term Category Software & AI Sources 3 Updated 5/5/2026 [Compare with another term](/compare?a=synthetic-data) Learn in 60 seconds Card Lesson Quiz Artificially generated data used to augment training, validation, or stress-testing of medical AI. - · FDA has explicitly noted both the promise and the limits of synthetic data for training and validation; transparent reporting is expected. - · Used to balance underrepresented subgroups, model rare events, or substitute for sensitive data - but introduces realism, leakage, and bias-amplification risks. Remember this Watch out: A common pitfall is generating synthetic data that fails to capture the true underlying statistical properties or rare events accurately, leading to models that perform poorly in real-world scenarios. Related terms - [Data Governance (AI/ML) ](/terms/data-governance) - [Algorithmic Bias and Fairness ](/terms/ai-bias-fairness) You may also need Auto-suggested from Software & AI and shared keywords. - [Model Card ](/terms/model-card) - [Algorithm Change Protocol(ACP) ](/terms/algorithm-change-protocol) - [Federated Learning ](/terms/federated-learning) - [Foundation Model (Healthcare) ](/terms/foundation-model-health) - [MLOps for Medical Devices(MLOps) ](/terms/mlops-medical-device) - [AI/ML-Enabled Medical Device ](/terms/ai-ml-device) [All Software & AI terms](/terms?cat=Software%20%26%20AI) From the Blue Goat network Related resources and services on this topic. - [ AI SaMD Insights How AI is changing SaMD - risk, regulation, and good machine-learning practice. ](https://ai-samd.com) - [ Med Device Cyber Podcast Conversations with medical device cybersecurity practitioners. ](https://mdcpodcast.com) MedTech Terms An authoritative, plain-language reference for the regulatory, quality, cybersecurity, and software terms that shape modern medical devices. 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