Advocacy - Lab Advocate
FDA recently published a set of guiding principles intended to promote the development of medical devices that use artificial intelligence and machine learning (AI/ML) technology. Developed in collaboration with Health Canada and the U.K.'s MHRA, the document is part of a broader effort to establish an internationally-harmonized regulatory framework for the quickly advancing field. The principles represent a starting point for further work, and the document expands on issues regarding possible biases of algorithms, applicability to clinical practice, and other concerns:
- Multi-Disciplinary Expertise Is Leveraged Throughout the Total Product Life Cycle
- Good Software Engineering and Security Practices Are Implemented
- Clinical Study Participants and Data Sets Are Representative of the Intended Patient Population
- Training Data Sets Are Independent of Test Sets
- Selected Reference Datasets Are Based Upon Best Available Methods
- Model Design Is Tailored to the Available Data and Reflects the Intended Use of the Device
- Focus Is Placed on the Performance of the Human-AI Team
- Testing Demonstrates Device Performance during Clinically Relevant Conditions
Advancing the application of data analytics technology with laboratory medicine and the delivery of healthcare is a key objective for AACC as part of its strategic plan. Over the summer, the association released a position statement outlining policy changes that would help move this objective forward. AACC is continuing to monitor regulatory developments as it works to advance this fast-moving field.