The primary goal of the life sciences industry is to improve access to treatment and increase positive healthcare outcomes for patients. In a constantly evolving landscape, the industry works to achieve this goal through research, development, and the manufacturing of pharmaceuticals, medical devices and biotechnological products — all of which emphasize patient safety, product quality and data integrity.
In this context, the advanced technologies used to design and manufacture today’s products seek to reduce errors and enhance patient care. As these devices become more sophisticated and widely utilized, there is a need for industry leaders to offer additional insights and understanding to ensure continued safety and compliance. Here is where software assurance plays a critical role.
Computer Software Assurance (CSA) is the result of a multi-year collaboration between the U.S. Food and Drug Administration (FDA) and leaders in the life science industry that is designed to raise quality of the products and enhance patient safety. Under the CSA program, all software or automated data processing systems that are used as part of production or the quality system must be safeguarded for software quality assurance in addition to testing for its intended use. CSA addresses the following pain points that are common with traditional Computer System Validation (CSV):
- Roadblocks to evolving automation
- Repetition of vendor efforts
- Burdensome documentation
- Abundance of production defects
- Evidence-based approach
- Test script and tester errors that account for 75% to 80% of total defects.
The benefits of computer software assurance
In September 2022, the FDA issued CSA draft guidance for the life sciences industry and for FDA staff to help streamline the adoption of new technologies, enabling companies to develop and deliver more effective and efficient products. As opposed to the traditional Computer System Validation (CSV), CSA focuses on critical thinking and targeted testing.
The new CSA guidelines enable manufacturers to focus more on patient safety and product quality by adopting a risk-based, data-driven approach based on objective analysis. The benefits of the FDA’s new CSA guidelines include:
- Strong emphasis on minimizing risks to patient safety and ensuring product quality by switching focus from documentation to critical thinking and testing
- Decrease in the volume of burdensome documentation
- Utilization of unscripted testing to reduce paperwork by approximately 80 percent
- Decline in production issues
- Adoption of cost-effective strategies
- Prevention of redundant testing
- Supports agile software development life cycle (SDLC) methodology
- Identification of factors that endanger patient safety, degrade product quality and compromise data integrity
- Supported by FDA and the International Society for Pharmaceutical Engineering.
The goal of this shift from CSV’s cumbersome evidence-based approach to CSA’s data-driven, risk-based approach is to increase the scope for innovation and automation within the life sciences industry. CSA allows manufacturers to determine the extent of testing based on process risk and product risk.
Successfully transitioning to CSA guidelines
To adapt to an increasingly technology-driven world, manufacturers and suppliers are transitioning from paper documentation to electronic records and other information technology solutions.
CSA facilitates the adoption of advanced technological solutions within the life sciences domain while offering a new approach to risk management. The steps under CSA guidelines are:
- Determine the potential patient/product/regulatory impact from functionality failure (i.e., direct, indirect, or none).
- Determine the functionality’s implementation method (i.e., custom, configured, or out of the box) and calculate the risk/impact on patient safety and product quality.
- Determine the functionality’s overall risk rating.
- Follow recommended testing activities based on the determined risk. For example, if the software does not impact patient safety or product quality, it is not necessary to perform the same level of testing required for a software that impacts patient safety or product quality.
Manufacturers in the life sciences industry are relying more on computers and automated processing systems to monitor and operate production, provide alerts to responsible personnel, and transfer and analyze production data.
To facilitate the process, the FDA recommends using CSA for software or automated data processing systems used as part of medical device production or the quality system to minimize defects during the software development life cycle (SDLC). Furthermore, CSA also provides flexibility and agility in ensuring that software or automated data processing systems are fit for intended use. This is accomplished by allowing manufacturers to adopt to new approaches such as risk-based testing, continuous performance, and data monitoring, as well as leveraging validation activities performed by other entities (i.e., developers and vendors).
The FDA asserts that these recommendations will help foster the adoption and use of innovative technologies that promote patient access to high-quality products and help manufacturers to keep pace with the dynamic, and rapidly changing technological landscape, while promoting compliance with procedures, guidelines, and regulations.
Ultimately, it is important for manufacturers within the life sciences industry to have a plan in place to ensure a successful transition to the new CSA guidelines.
A roadmap to success for computer software assurance
The CSA guidelines are designed to advance the life science industry and provide a detailed road map that encourages critical thinking early in the process, implements risk-based approach during planning stages, and leverages vendor documentation and testing in the validation process. It will be imperative for all stakeholders to accept and support these new guidelines for the transition to be successful. Manufacturers that embrace the CSA guidelines will improve innovation and quality in life sciences while supporting industry and organizational success. Not surprisingly, there will be a learning curve involved with the adoption of the proposed guidelines.
About the Author:
Vamshi Mannem has over 12 years of experience in the life sciences industry with an emphasis on computer system validation. His knowledge includes expertise in validating enterprise applications that serve various departments such as quality, R&D, regulatory, clinical, manufacturing, sales and marketing. He is a member of Rho Chi Society. For more information, please email firstname.lastname@example.org.
Filed Under: clinical trials, Drug Discovery, Drug Discovery and Development