# Overview of the FDA’s New Draft Guidance on Predetermined Change Control Plans
In March 2023, the U.S. Food and Drug Administration (FDA) released a draft guidance document titled **”Predetermined Change Control Plans for Artificial Intelligence/Machine Learning (AI/ML)-Enabled Device Software Functions”**. This guidance represents a significant step forward in the regulatory framework for medical devices that incorporate artificial intelligence (AI) and machine learning (ML) technologies. The document outlines the FDA’s expectations for manufacturers who wish to implement changes to AI/ML-enabled software after the device has been cleared or approved, without requiring additional premarket submissions for each modification.
This article provides an overview of the key elements of the FDA’s draft guidance on Predetermined Change Control Plans (PCCPs), its implications for the medical device industry, and the potential benefits and challenges associated with this new regulatory approach.
## Background: AI/ML in Medical Devices
AI and ML technologies have the potential to revolutionize healthcare by enabling medical devices to continuously learn from new data and improve their performance over time. These technologies are increasingly being integrated into a wide range of medical devices, from diagnostic tools to therapeutic systems. However, the dynamic nature of AI/ML presents unique regulatory challenges, particularly when it comes to managing post-market changes.
Traditionally, medical device manufacturers are required to submit a new premarket notification (510(k)) or premarket approval (PMA) application to the FDA whenever they make significant changes to a device’s design, performance, or intended use. However, AI/ML-enabled devices are designed to evolve over time, making it impractical to submit a new application for every software update or algorithm modification.
To address this challenge, the FDA has introduced the concept of **Predetermined Change Control Plans (PCCPs)**, which allow manufacturers to outline in advance the types of changes they intend to make to their AI/ML-enabled devices and the methods they will use to ensure the safety and effectiveness of the device after those changes are implemented.
## Key Elements of the Draft Guidance
The FDA’s draft guidance on PCCPs provides a framework for manufacturers to propose and implement changes to AI/ML-enabled device software functions in a controlled and transparent manner. The guidance outlines several key elements that manufacturers should include in their PCCPs:
### 1. **Description of the Changes**
Manufacturers must provide a detailed description of the types of changes they anticipate making to the AI/ML-enabled device software. These changes may include updates to the algorithm, modifications to the training data, or adjustments to the device’s performance parameters. The description should also specify whether the changes are intended to improve the device’s accuracy, expand its intended use, or address emerging safety concerns.
### 2. **Risk Management and Mitigation**
The PCCP should include a comprehensive risk management plan that identifies potential risks associated with the proposed changes and outlines strategies for mitigating those risks. This may involve conducting additional testing, validation, or clinical studies