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Embrace the Future of Software Assurance with Inteldot's CSA Expertise

Traditional software validation methods can prevent innovation. Exhaustive documentation and one-size-fits-all testing can slow down development and consume valuable resources. At Inteldot, we empower companies to achieve the highest quality standards while unlocking their full innovation potential through Computer Software Assurance (CSA).

Why move from CSV to CSA?

CSA is a risk-based approach to software assurance specifically designed for production and quality systems. Unlike traditional Computer System Validation (CSV), CSA emphasizes critical thinking. CSA is a set of methods, processes, and activities that verify software systems work properly, safely, and efficient. 

Extensive documentation requirements, which are frequently focused on audit preparedness rather than actual system comprehension, can cause a compliance burden, restricting innovation and delaying the delivery of life-saving solutions. CSA provides a more streamlined path: 

  • RISK-BASED FOCUS: CSA prioritizes software elements critical for product quality and patient safety. This reduces unnecessary documentation and streamlines the audit process.

  • EARLY RISK IDENTIFICATION: By proactively identifying and mitigating software risks, CSA minimizes the potential for delays and rework later in the development cycle.

  • STREAMLINED PROCESSES: Clear and concise CSA practices eliminate redundant procedures and ensure efficient compliance management

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The FDA recognized the power of CSA

The US Food and Drug Administration (FDA) issued draft guidance for CSA in September 2022. This shows the FDA's growing acceptance of CSA as a robust and efficient approach to ensuring software quality within the life sciences industry. By adopting CSA, your company demonstrates its commitment to meeting the highest regulatory standards while optimizing its development processes.

Reduced paperwork and streamlines audits
Early risk mitigation for fewer delays
Focus on innovation through resources optimization

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