A question that investors frequently ask of emerging growth life sciences companies is whether they have considered how to monetize the data they will inevitably collect in the development, marketing and sale of their service or product. Data merely existing in a compilation can have value; analytics can increase that value by orders of magnitude. Beyond compilation and analytics is the use of data to provide direct treatment or services. Using artificial intelligence (AI) (smart machines that are developed to do work normally done by humans) and machine learning (ML) (machines that are designed to teach themselves), data can be used to produce products and services of great value, such as customized genomic cancer treatments. These tools, products and services are a rapidly emerging growth area in the life sciences, and the Food and Drug Administration has taken note.

On April 2, the FDA released a discussion paper titled “Proposed Regulatory Framework for Modifications to Artificial Intelligence/Machine Learning (AI/ML)-Based Software as a Medical Device (SaMD).” The International Medical Device Regulators Forum defines SaMD as software intended to be used for … medical purposes … without being part of a hardware medical device. Thus, the software can perform its medical purpose without being tied to a specific piece of hardware. The discussion paper recognizes the challenges in regulating AI/ML SaMD, which learns and adapts over time. Essentially, the FDA is examining how to regulate SaMD that is designed to, over time, evolve into a product different from the one that was originally found to be safe and effective by the FDA’s regulatory process and cleared for market.

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