Validating FDA Regulated System supporting medical device

Overview

The life science industries continue to embrace new technology to improve delivery of quality products in compliance with FDA. In addition to some trends toward making use of cloud services, Software-as-a-Service (SaaS) solutions, and other technical innovations that have more recently begun to be used more heavily in life science companies.

Artificial Intelligence (AI) and Machine Learning (ML) are beginning to find a presence at these companies. We are seeing much more activity related to AI use in software applications used to develop, produce, test, and manage life science products, particularly medical device and Software-as-a-Medical Device (SaMD) products with quality and compliance.

Medical devices using AI are designed to analyze vast amounts of data to generate clinical insights. This means that the company’s quality management system (QMS) must ensure consistent production and control of manufacturing and quality systems, and involves routine inspections and audits.

The development and production of medical device and SaMD products require computer system validation, 21 CFR Part 11 (Electronic Records and Electronic Signatures) compliance, and data integrity assurance.

The Verifying Accurate Leading-Edge Development Act, or Valid Act is pending in the US Congress, and will codify the “firm-based” approach to regulation. FDA will oversee methods used for technology development and validate reliability rather than decoupling the AI product’s construction. By ensuring robust systems are in place, FDA can enhance overall safety and effectiveness of medical devices produced.

Rapid cycles of innovation inherent in products due to constant modification based on new information available pose challenges. Large Language Models (LLMs) have demonstrated substantial semantic medical knowledge and the ability to perform work that will accelerate the submission approval process.

LLMs will boost efficiency, but input data must be quality-checked. Industry must develop adequate standards and controls, evaluating AI algorithm models under the specific intended use of a device. Ultimately, industry will be able to identify new product candidates and plan, execute, and analyze data from clinical trials.

Learn more about how FDA and life science companies are using AI. It is critical at a time of rising demand for healthcare and physician shortages. Leveraging comprehensive data systems will lead to greater efficiency in diagnosis and treatment planning.

For SaMD products, there are several guidance documents from FDA and the International Medical Device Regulators Forum that will be beneficial in understanding how to make changes to these products safely through a method using SaMD Pre-Specifications (SPS) and an Algorithm Change Protocol (ACP) to assess the potential risk and impact of a change.

Learn about the FDA’s AI/ML SaMD Action Plan, encouraging harmonization among technology developers on the development of GMLP). This is part of FDA’s mission to define new policies and enable innovation while protecting public health.

You will also learn about the Total Product Lifecycle (TPLC) Approach for SaMD regulation. This is a new paradigm focused on the assessment of an organization in terms of their software design, development, testing and monitoring activities. 

We’ll provide an overview of computer system validation, including the FDA guidance on Computer Software Assurance (CSA), and the latest GAMP®5, 2nd Edition that aligns with CSA. We’ll walk you through the Software Validation and Maintenance approach that will bring clarity to what FDA is looking for, primarily allowing companies to manage risks from changes, while enabling improvement of performance and advancing patient care.

Why Should You Attend

Providing safe and effective medical devices, drugs, and other FDA-regulated products is in the best interests of all those involved in the development, manufacturing, testing, and distribution of these products. You will learn about projects going on in industry and at FDA that take advantage of Artificial Intelligence (AI), Machine Learning (ML) and Large Language Models (LLMs), such as ChatGPT.

With newer technologies such as AI in the mix, it means opportunity for greater efficiency and efficacy, but also poses more challenges for companies that develop, test, and support software applications in the life science industries.

In this webinar, you will learn just how AI, ML and LLMs, such as ChatGPT can increase efficiency and effectiveness of software development life cycle (SDLC) activities, enabling the delivery and support of computer solutions and new innovative products that will drive industry over the coming years.

This webinar is intended for those working in the FDA-regulated industries, including pharmaceutical, medical device, biological, animal health and tobacco. Functions that are applicable include research and development, manufacturing, Quality Control, distribution, clinical testing and management, adverse events management and post-marketing surveillance.

You should attend this webinar if you are responsible for planning, executing or managing the development or implementation of any system governed by FDA regulations, or if you are maintaining or supporting such a system. Learn by reviewing industry best practices and knowing where to gather key information to help you move forward with these technologies quickly and in compliance with FDA.

Webinar Takeaway

During the webinar, we will discuss the following:

• Learn about how AI is increasing in use in the life sciences industries, and how companies are leading the way to delivering more effective, safer, and more beneficial Medical Device & Software-as-a-Medical Device (SaMD) products as a result.
• Learn about the potential risks and challenges related to AI, ML and LLMs, such as ChatGPT.
• Learn about the challenges and vulnerabilities facing industry today, and how these new technologies can provide steps forward.
• Learn about FDA’s considerations for adapting its review process for AI-enabled software used to develop, manufacture & maintain medical device & SaMD products that have the ability to evolve rapidly in response to new data, sometimes in ways difficult to foresee.
• Learn how and under what circumstances products relying on AI are regulated by FDA.
• Learn about the potential impact and risk threatening data, processes, products, and ultimately patients based on these.
• Understand how to ensure benefits of medical device & SaMD products outweigh risks.
• Learn what FDA is doing to confront the increase in cyberthreats posed with the advent of newer technologies, particularly with use of medical device & SaMD products in a network setting such as a hospital or clinic, and what further work may be done.
• Understand how FDA, Congress, technology developers, and health care industry must work together to forge this new path and lead to a deeper and broader application of AI in operational processes in today’s FDA-regulated companies.
• Understand current industry best practices and recommendations for improving compliance of products that leverage AI in operational processes.
• Learn about industry best practices for implementing, validating, meeting FDA Part 11 and data integrity requirements, as AI applications improve operational efficiency and effectiveness in the process.
• Q&A

Who Will Benefit

Personnel in the following roles will benefit:

• Information Technology Analysts
• Information Technology Developers and Testers
• Software Quality Assurance Professionals
• QC/QA Managers and Analysts
• Analytical Chemists
• Compliance and Audit Managers
• Laboratory Managers
• Automation Analysts
• Manufacturing Specialists and Managers
• Supply Chain Specialists and Managers
• Regulatory Affairs Specialists
• Regulatory Submissions Specialists
• Risk Management Professionals
• Clinical Data Analysts
• Clinical Data Managers
• Clinical Trial Sponsors
• Computer System Validation Specialists
• GMP Training Specialists
• Business Stakeholders/Subject Matter Experts
• Business System/Application Testers
• Vendors responsible for software development, testing and maintenance
• Vendors and consultants working in the life sciences industry who are involved in computer system implementation, validation and compliance

Background

The life science industries, including pharmaceutical, medical device, biotechnology, biological, and tobacco and tobacco-related products continue to embrace new technology to improve delivery of quality products in compliance with FDA. In addition, we’ve seen some trends toward making use of cloud services, Software-as-a-Service (SaaS) solutions, and other technical innovations that have more recently begun to be used more heavily in life science companies.

Artificial Intelligence (AI), Machine Learning (ML) and Large Language Models (LLMs), such as ChatGPT are beginning to find a presence at these companies. While life science companies tend to lag behind other markets in using these technologies, they are catching up and we are seeing much more activity related to AI use in software applications used to develop, produce, test, and manage life science products with quality and compliance.

As the pace of technological innovation and evolution becomes more intense, there is a critical need for computer system validation, 21 CFR Part 11 (Electronic Records and Electronic Signatures) compliance, and data integrity assurance to continue in environments where artificial intelligence (AI) and machine learning (ML) are becoming prevalent.