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Empowering pharma companies to streamline validation, reduce risk, and embrace digital innovation with confidence.
Computer Software Assurance (CSA) is a modern, risk-based validation approach introduced by the FDA to replace the traditional Computer System Validation (CSV) model. It focuses on critical thinking, risk assessment, and efficient testing—specifically for non-product software used in regulated environments.
Pharma companies rely on a wide range of software for manufacturing, clinical trials, supply chain, quality systems, and compliance.CSA helps ensure these systems are validated efficiently while maintaining regulatory compliance and product quality.
| Principle | Description |
|---|---|
| Risk-Based Thinking | Prioritizes validation efforts based on the impact on patient safety and product quality. |
| Critical Thinking | Encourages process owners and quality teams to decide the level of assurance needed. |
| Efficient Testing | Supports unscripted and exploratory testing where appropriate—reducing redundant documentation. |
| Data Integrity Focus | Ensures systems that manage GxP data are reliable, secure, and audit-ready. |
| Reduced Documentation | Eliminates unnecessary paperwork that does not add compliance or quality value. |
| Encourages Innovation | Supports adoption of new technologies, cloud platforms, and AI/ML systems by easing validation burdens. |
Predactica’s AI enables intelligent automation of CSA (Computer Software Assurance) validation in the pharmaceutical industry by leveraging advanced machine learning, natural language processing, and agentic workflows.
Use Case: Ensuring data accuracy and compliance in manufacturing records.
Example: Validating an EBR system used to document each step in the production of a drug, helping reduce manual errors and audit risks.
Use Case: Managing sample tracking, results, and data reporting in labs.
Example: Using CSA to focus assurance on high-risk functions such as test result accuracy, while applying streamlined testing to administrative features like login.
Use Case: Supporting deviation, CAPA, and document management processes.
Example: Using CSA to prioritize assurance on workflows for deviation approvals over cosmetic UI updates.
Use Case: Coordinating clinical trial planning and operations.
Example: CSA helps validate the integrity of patient randomization and data collection processes, ensuring trial data quality.
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ML powered data analysis tools from Predactica®
At Predactica®, we aim at empowering businesses with ML and AI tools that can be used by citizen data scientists. Our tools are easy to use, give out actionable insights, and use transparent, explainable ML models.
