Introduction
Software as a Medical Device (SaMD) represents the intersection of two historically separate worlds: software development (rapid iteration, continuous deployment, near-zero marginal cost) and medical device regulation (rigorous evidence requirements, fixed product definitions, lengthy review timelines). As MedTech companies increasingly layer software onto hardware platforms and as standalone AI diagnostic tools proliferate, understanding SaMD regulation has become essential for healthcare banking.
What Qualifies as SaMD
- Software as a Medical Device (SaMD)
Software that performs a medical function on its own, running on general-purpose computing platforms (smartphones, tablets, cloud servers, desktop computers) rather than being embedded in a dedicated hardware device. Key distinction: software IN a medical device (e.g., the operating software of a CT scanner) is regulated as part of the hardware device. SaMD is software that IS the medical device. Examples include AI algorithms that detect diabetic retinopathy from retinal images, apps that calculate insulin dosing, and cloud-based tools that analyze pathology slides for cancer detection.
The FDA uses a risk-based framework for SaMD that considers the significance of the information provided (treating/diagnosing vs. informing) and the seriousness of the healthcare situation (critical vs. non-serious). Higher-risk SaMD (diagnosing critical conditions) faces more rigorous requirements, while lower-risk SaMD (informing about non-serious conditions) has a lighter path.
The AI/ML Device Landscape
The FDA has authorized over 1,250 AI/ML-enabled medical devices as of early 2026, with the pace accelerating rapidly. The vast majority (approximately 80%) have been authorized through the 510(k) pathway, with radiology representing the largest category (over 75% of AI authorizations).
| Category | Share of AI Authorizations | Example Applications |
|---|---|---|
| Radiology | ~75% | CT/MRI analysis, fracture detection, stroke triage |
| Cardiovascular | ~10% | ECG interpretation, arrhythmia detection |
| Pathology | ~5% | Digital pathology, cancer cell detection |
| Ophthalmology | ~3% | Diabetic retinopathy screening |
| Other | ~7% | Dermatology, gastroenterology, neurology |
Investment Implications
SaMD businesses have a unique financial profile that combines the best characteristics of software companies with the regulatory constraints of MedTech:
Software-like economics. Gross margins of 85-95% (vs. 55-70% for hardware MedTech), near-zero marginal cost per additional user, and the potential for rapid scaling once cleared. SaaS-style pricing models (per-study, per-patient, or subscription) create recurring revenue streams.
Regulatory constraints on iteration speed. Unlike consumer software, SaMD cannot be updated continuously without regulatory consideration. Significant changes may require new 510(k) submissions or PMA supplements. This regulatory friction slows the product development cycle relative to non-medical software but is far faster than hardware device development cycles.
The next article covers procedure volume and ASP modeling, the core revenue drivers for device companies.
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