The Expanding Landscape of Software as a Medical Device

The Software as a Medical Device (SaMD) market is experiencing explosive growth. These software applications, designed for medical purposes from diagnosis and prevention to monitoring, treatment, and even alleviation of disease, are able to fill gaps in an overburdened, understaffed healthcare system.

Galen Data reported that the global market value for SaMD was $1.2 billion in 2022. It is expected to increase to $5.4 billion by 2032, with a compound annual growth rate (CAGR) of 16.7%. This growth is driven by several factors, including advancements in artificial intelligence (AI) and machine learning (ML), increased adoption of cloud computing, focus on personalized medicine, and the rise of the female healthcare consumer.

Current State of Affairs

As of April 2024, we have been able to find and categorize 530 FDA-cleared SaMD products across 18 categories, including three products we’ve led research and design for here at Guidea. This list is, in part, from the FDA’s list of AI enabled medical devices, and also includes FDA-cleared digital therapeutics (DTx) and other FDA-cleared SaMD that is not AI enabled. 

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The most prominent category for SaMD innovation and clearance is:

• Radiology: With over 300 FDA-cleared SaMD applications, radiology has the highest number of FDA-cleared applications. These solutions range from AI-powered image analysis tools that can detect abnormalities in mammograms, like DeepLook Medical, to computer-aided detection (CAD) systems that assist radiologists in interpreting complex scans.

Other active categories include:

• Cardiology: The second largest category of SaMD applications focuses on cardiovascular health. SaMD solutions in this space include mobile apps for monitoring heart rhythm and blood pressure, as well as implantable devices that can detect and respond to cardiac emergencies.
• Diabetes Management: These products help diabetic patients track blood sugar levels, monitor insulin intake, and receive automated insulin dosing recommendations. This is a prime example of Digital Therapeutics (DTx), a rapidly growing field that leverages SaMD to deliver evidence-based interventions for chronic conditions.
• Neurology: These solutions span multiple areas including:
  • Mental Health: Offers solutions for anxiety, depression, sleep disorders, and ADHD. These might include tools for self-management, therapy support, medication adherence, and cognitive training.
  • Neurological Disorders: These apps can play a significant role in managing conditions like epilepsy, Parkinson's disease, and multiple sclerosis. Tools can help with symptom tracking, medication reminders, and even tremor control.
  • Cognitive Decline and Dementia: DTx and SaMD are being explored for cognitive training, memory improvement, and managing the daily lives of people with dementia.
  • Stroke Rehabilitation: Apps can be used for motor skill rehabilitation, speech therapy, and cognitive function improvement after a stroke.

Predictions of the Future

While we can’t say for certain what will be cleared next, we can explore the pipeline. We took a deep dive into the ARPA-H Nationwide Health Innovation Network, the USPTO, and ClinicalTrials.gov to see the Request for Solutions (RFS), grant funded projects, patents filed, and clinical trials. Check out our predictions for The Future of SaMD: A Glimpse of What's To Come. 

How we help innovative companies launch effective SaMD products

Guidea partners with leading biopharma, life science, MedTech, and healthcare companies to design and validate products that measurably improve people’s health. Our repeatable process for innovation provides a reliable path to deliver effective and engaging products for patients, providers, payers, and employers. Contact us to learn more about our work with DTx and SaMD pioneers: WellDoc, Somryst, and Cognoa.

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Sources:

MedTech Intelligence: FDA-Cleared SaMD by the Numbers

FDA Publishes Updated list Of 521 Authorized AI Enabled Medical Devices

UFDA: Artificial Intelligence and Machine Learning (AI/ML)-Enabled Medical Devices