For life sciences businesses that manufacture regulated products, software validation is essential. However, this complex and time-consuming process can take time to manage.
It has forced regulated companies to make tradeoffs, such as delaying software upgrades or avoiding customizations that require initial validation and revalidation upon upgrade. It prevents them from unlocking the full potential of their new technology.
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Functional Requirements
Software validation in life sciences is a critical process that ensures the software used in developing, manufacturing, and testing medical products is reliable, accurate, and secure. This is essential for protecting patient safety, data integrity, and product quality, adhering to strict regulatory requirements. For life sciences businesses, the need to validate computer systems is crucial. Any software that creates, modifies, maintains, archives, retrieves, or transmits FDA-regulated records must be validated. This includes compliance software used to manage Quality Management programs and enterprise resource planning (ERP) systems that handle all aspects of business operations.
Firms should employ a risk-based approach to get the most value from a validation effort. It satisfies the reason behind validation without smothering businesses in bureaucratic red tape. A firm assessing its risk can determine what steps are needed and how to perform them, thus minimizing time and costs.
Using a risk-based approach can also help firms avoid having to complete all the traditional steps of validation, including Installation Qualification (IQ), Operational Qualification (OQ), and Performance Qualification (PQ). Choosing a vendor that has validated its software before offering it as a service can reduce testing and documentation costs by enabling a company to skip the IQ and OQ and start with PQ instead.
Companies should automate their software validation processes to improve efficiency further. A robust EQMS can provide automated validation scripts that run against an entire app portfolio and deliver IQ, OQ, and PQ system tests with the click of a button. It eliminates manual re-testing after each software upgrade, saving time and cost.
Risk Analysis
While many software vendors claim life science expertise, the best way to assess this is by their willingness to support validations with automated scripts. It eliminates tedious manual testing and allows teams to focus on critical thinking-based improvements.
The quality of their software is directly tied to patient safety for pharmaceutical, biotechnology, medical device, and life sciences companies. Computer systems must be validated for data collection, clinical study submissions, or other critical processes to ensure accuracy and compliance with FDA guidelines.
A sound quality system will allow for a high level of automation, making it easier to validate software upgrades without impacting the integrity of 21 CFR Part 11 records and other critical systems. Some vendors significantly lower the effort and time to complete validations while still meeting FDA requirements.
Handling business complexity and rapid technological change is challenging for life sciences, healthcare, and medical device companies. A solution that enables them to quickly and continuously validate and revalidate apps as they upgrade will provide significant value, helping them accelerate growth, reduce industrial risks, and meet regulatory compliance requirements. Software validation helps to achieve these goals by merging logic-driven technical team members with results-focused business teams, resulting in something that meets functional requirements, supports critical business processes and goals, and mitigates industrial and cybersecurity risks.
Testing
For life sciences firms, validation must ensure that software that maintains GxP records does so with accuracy, reliability, integrity, availability, and authenticity. Unfortunately, many of these organizations rely on validation methods that need to be updated, which is time-consuming and resource-intensive, forcing tradeoffs that prevent them from deploying best-of-breed apps.
For example, the traditional computer system validation (CSV) process involves 80% of staff time spent on documentation and testing. It could be more efficient and effective, particularly for life science software solutions that require a more significant focus on critical thinking and assurance activities. However, the FDA’s latest draft guidance recommends a risk-based approach to CSV called computer software assurance (CSA), which enables teams to keep pace with technology and stay GxP compliant simultaneously.
With CSA, users will test a software application to verify that it meets their business requirements and intended functionality. It will include IQ, OQ, and PQ system tests, which are documented and logged. Deviations found during testing will be investigated and tested again to ensure they are fixed before the application is used in a production environment. It will help reduce timelines and costs while reducing risks of regulatory action. Life science companies using best-of-breed applications and a continuous validation strategy can unlock the full potential of their adopted technology without the need for lengthy initial and re-testing.
Documentation
Software validation is a crucial task in life sciences – it ensures that the applications regulated companies use to maintain records perform as intended and meet quality, safety, and compliance standards. However, the process can be tedious and time-consuming, mainly when life science companies use multiple stand-alone software tools.
The traditional computer system validation (CSV) approach includes manual documentation processes, lengthy testing scripts, and many screenshots – sometimes tens of thousands for a single validation protocol. Unfortunately, this can result in a heavy burden on teams and hinder a business’s ability to keep up with technological change and handle rapid growth.
FDA-regulated life sciences businesses must be able to quickly adapt, grow, and meet the demands of the business environment. To do so, they must have suitable systems and processes. This is where the value of a risk-based and critical thinking approach to CSV comes in.
Regulatory compliance requires computer systems for data submissions, manufacturing, quality management, traceability, recall and hold functionality, non-conformance reporting, and more. It is also essential for clinical studies to be conducted electronically, as this helps ensure that the data collected is accurate and reliable. A well-designed software validation strategy will help companies avoid errors, inconsistencies, and failures to comply with the FDA and ICH guidelines.
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