5 steps to successfully implement a risk-based approach to validation
Quality assurance experts and other life sciences professionals strive to deliver value to patients and businesses by defining and implementing parameters and best practices critical to quality. These teams share a focus on reducing patient risk in environments that are under pressure to continuously improve to meet the evolving demands of regulators, businesses and customers. This daunting labyrinth requires a complex strategy to map out a safe and timely way through the maze. While controlled change is vital to good governance practices, change does not start. Organizations and individuals charged with overseeing the validation of computer systems must also evolve.
Such work environments require business capabilities that drive the need for new technologies and new ways of working. Often, new technologies and supporting processes present potential vulnerabilities and threats that must be addressed head-on to ensure patient safety parameters are met. Businesses also need to protect the information flowing through these tools and processes so that it reaches only those individuals or entities for whom it is intended. Computer systems quality assurance professionals are well positioned to work with test developers, as well as information security management professionals, to design risks from new systems by creating forward-thinking strategies that identify, assess, monitor, and address risks .
Computer Software Assurance (CSA) is a model that innovative companies use to consistently and repetitively deliver excellence.
For companies new to this journey, bringing key stakeholders and subject matter experts together with the common goal of patient safety and clearly defined parameters for compliance supports an innovative culture based on openness and trust. This makes it possible to create new strategies and optimized processes for projects, which may have stalled in the past, through the implementation of newer technologies. Such a model aligns teams for success by equipping them to successfully navigate risk and become effective in surfacing greater efficiencies bringing safe and effective therapies to the market.
Validation methods that are agile, well managed and monitored increase project success, save time and free up resources to do more impactful work. A successful CSA program is proficient in assessing systemic risk and creating control frameworks to monitor and manage activities that impact patient safety, product quality, end-user and customer experiences, as well as third-party risks. CSA requires a rethink of the status quo, but many organizations are still trapped in linear processes enshrined in SOPs. They remain blind to tools and new ways of working that would help them map out new routes to improve product quality and remove unnecessary processes.
The past – Focus on regulatory documentation, rather than product quality, production efficiency and patient safety
For years, the focus of Computer System Validation (CSV) processes has been on producing accurate and approved documentation to present information to auditors. Auditors, like the FDA, need evidence and data. Therefore, the CSV methodology inspires a compliance mindset rather than an innovative one. As such, the existing CSV methodology leads manufacturers to spend approximately 80% of their time producing documentation and only 20% of their time actually testing the software. Rather than guaranteeing product quality, these extensive documentation requirements have become a bottleneck and burden for life sciences companies, discouraging investment in more automated IT solutions. While documentation will always be an essential part of the process, it is more important to have a safe, high quality product that meets patient needs, rather than robust documentation that passes an audit cycle.
CSV guidelines prioritize documentation, primarily to appease auditors, which can be both time-consuming and costly. This emphasis on documentation hinders the application of critical thinking during the validation process, along with opportunities to improve automation through system modernization.
CSA enables organizations to tailor their validation efforts because it is based on risks that have been assessed and classified, which can streamline processes and save resources. This means that while all aspects of the systems used in manufacturing must be tested, only components essential to product quality and patient safety must undergo full validation. This frees up testing and validation resources to focus on more value-added activities. CSA can help start-ups and established life sciences companies by providing guidance in managing validation processes to support the changing landscape of digital transformation. The travel time from CSV to CSA is critical as it ensures the company keeps pace with technological innovation. Electronic solutions allow for a more connected, compliant and efficient organization.
How much time do your resources spend on low-risk, low-probability replays? How much time are your resources documenting without assessing and classifying the risk, then matching the amount of testing due to risk classification? What if their focus was on more testing, testing for proof of concept or proof of intended use to find potential unforeseen issues prior to documentation? How much time could be saved in a project lifecycle if validation efforts techniques were planned in advance? With CSA, the days of creating validation documentation for the sake of documentation are long gone. Real testing. Real time. More automation. Less documentation. Is the life sciences industry ready to make the journey?
The Risk Journey
Software vendors and other technology for life sciences organizations are made to be easy to implement. Out-of-the-box applications enable companies to be more efficient and strategic, while also complying with regulations. Applications for use in regulatory environments must be reviewed and then validated if there is any GxP impact. Cloud-based applications are created and often managed with strict regulations, standards and controls. The key here is assessing the governance, risk controls, and information security practices used in software creation and ongoing monitoring. The CSA model emphasizes testing the functions used for their intended purpose. This testing methodology ensures organizations understand the real risks and helps maintain data integrity along with product quality and safety.
The life sciences industry has changed significantly over the years and product launch timelines have been reduced from years to months. Testing and validation efforts require comparable improvements in project lead times while demonstrating real risk reductions. CSA reduces documentation while spending more time implementing other improvements in the systems management lifecycle.
What stops the journey to CSA?
The industry knows that electronic tools work; we understand risk and risk classification. So why is it difficult to move from CSV to CSA? Is the industry holding onto legacy processes because they are ‘secure’ practices? CSA does not mean less safe, but more efficient with proper testing based on risk assessment. Change is intimidating in the life sciences environment; a small change can set off a paper blizzard that can take weeks to clear a path. To be more efficient and to keep pace with innovative technologies in the digital transformation landscape, the adoption of CSA is critical for the industry.
Steps to a successful transition
Organizations following the CSA approach can reduce costs and increase profits as it helps them keep their validation efforts sized for their intended use. It allows them to focus on quality throughout the product lifecycle, from concept to retirement. Not only can it reduce validation time, it can also provide a competitive advantage.
To switch to CSA, we recommend the following:
As the FDA prepares to release its new CSA guidelines, life sciences companies need to be proactive and develop a strategy for adopting the new CSA methodology that focuses on patient safety, product quality and data integrity.