FDA issues first guidance on AI in medicine development
FDA Commissioner Robert Califf
The FDA has responded to the increasing use of artificial intelligence (AI) in the discovery and development of drugs and biologics by publishing its first provisional guidance on the technology's use in regulatory filings.
According to the US regulator, the use of AI in drug development and in regulatory submissions has "exponentially increased" since 2016, and is being deployed in a host of ways to generate data or information on the safety, effectiveness, or quality of a drug or biological product.
Commissioner Robert Califf said that, with appropriate safeguards in place, AI has "transformative potential to advance clinical research and accelerate medical product development to improve patient care."
The draft guidance – which is open for comment until 7th April – proposes a risk-based assessment framework that drug developers can use to establish the credibility of an AI model for its intended use. Examples of uses could include predicting patient outcomes, improving understanding of predictors of disease progression, and analysing large datasets from sources like real-world studies or digital health technologies.
At the heart of the guidance is the concept of 'context of use' (COU), which defines how an AI will be used to address a "question of interest," according to the document. It describes a risk-based framework for sponsors to assess and establish the credibility of an AI model for a particular COU and communicate that to the regulator.
According to the FDA, it draws on the reviews it has carried out on drugs and biologics with AI components in recent years, but – with the technology still in its infancy – the agency recommends that sponsors engage with it early on in the development process to get feedback on credibility.
The FDA action follows the finalisation of a 'reflection paper' by the EMA last year, setting out the EU regulator's thinking on the use of AI in the medicinal product lifecycle.
Medical device advice
Meanwhile, the US agency has also just published new guidance on developing and managing AI-enabled medical devices, laying out a total product lifecycle (TPLC) approach that should consider elements such as user interface and labelling, data management, device performance monitoring, and cybersecurity.
Troy Tazbaz, director of the Digital Health Center of Excellence in the FDA's Center for Devices and Radiological Health, said in a statement that it has already authorised more than 1,000 AI-enabled devices to date.
He added, however, that "as we continue to see exciting developments in this field, it's important to recognise that there are specific considerations unique to AI-enabled devices."
The draft guidance "brings together relevant information for developers, shares learnings from authorised AI-enabled devices, and provides a first point-of-reference for specific recommendations that apply to these devices, from the earliest stages of development through the device's entire life cycle."
