AI/ML-Based SaMD Framework

The US Food and Drug Administration’s proposed regulatory framework for artificial intelligence- (AI) and machine learning- (ML) based software as a medical device (SaMD) is fascinating in what it exposes about the uncertainty around the near-term future of a lot of industry 4.0 initiatives in pharmaceuticals and medical devices.

While focused on medical devices, this proposal is interesting read for folks interested in applying machine learning and artificial intelligence to other regulated areas, such as manufacturing.

We are seeing is the early stages of consensus building around the concept of Good Machine Learning Practices (GMLP), the idea of applying quality system practices to the unique challenges of machine learning.

John Oliver on Medical Devices

I firmly believe that quality and ethics go hand-in-hand, and frankly it shakes some of my confidence on my profession when I read of organizations that supposedly subscribe to quality principles and standards (such as the ISOs) still not meeting the grade.

There are four widely accepted principles in biomedicine, which applies equally to medical devices and pharmaceuticals:

  • Principle of respect for autonomy
  • Principle of nonmaleficence
  • Principle of beneficence
  • Principle of justice

It seems a failure of ISO 13458 that adherence to this quality standard does not lead to results aligned to these four principles. It should surprise no one who knows me that this is one of the reasons I support strong regulations in this space.


  • Beauchamp T, Childress J. Principles of Biomedical Ethics, 7th  Edition. New York: Oxford University Press, 2013