Partnership Announcement: Assurea and Seeq

Assurea and Seeq have partnered to help pharma and biotech organizations adopt Seeq for Pharma within GxP-regulated environments. Seeq for Pharma helps pharmaceutical and biotech teams use advanced analytics and monitoring to gain insights from process and manufacturing data, improve process performance, monitor quality, and support reporting across regulated operations. Assurea will serve as the

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Runtime Verification and Assurea Partner to Strengthen Software Safety for Medical Devices, SaMD and Artificial Organs

The partnership brings together formal verification expertise and practical implementation support for companies creating safety-critical medical technologies. [Utah/North Carolina, August 18, 2026] — Runtime Verification and Assurea have announced a new partnership to help medical technology companies strengthen the safety, reliability and regulatory readiness of software used in medical devices, Software as a Medical Device

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Case Study: Using AI Analytics to Transform GxP Periodic Reviews

27 periodic reviews. 650+ documents analyzed. One clear view of system health. Periodic reviews are intended to answer a relatively simple question: Is this GxP system or piece of computerized equipment still operating in a controlled and appropriately validated or qualified state? Getting to that answer is rarely simple. A reviewer may need to look

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Preparing for Your First Digital System Implementation: A Practical Guide for Growing Biotech Companies

For a growing biotech company, implementing the first major digital system is an important milestone. Paper records, spreadsheets, shared drives, and disconnected tools that worked during early growth may no longer support increasing operational complexity, regulatory expectations, or future scale. The natural response is often to start evaluating software. But selecting an eQMS, LIMS, LMS,

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AI Manufacturing Intelligence for Technology Transfer: Reducing Manual Master Batch Record Reviews

How AI-powered document analytics helps manufacturing teams compare complex documentation, identify process differences, and accelerate technology transfer while keeping GMP decisions under human oversight. Technology Transfer Is Still a Documentation-Intensive Process Successful technology transfer is about far more than moving a manufacturing process from one facility to another. It requires ensuring that manufacturing knowledge is

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Validation of Veeva Vault Quality for a Global CDMO

How Assurea validated a U.S. deployment of Veeva Vault Quality and established a reusable validation framework for future global site rollouts. Project Overview When a global Contract Development and Manufacturing Organization (CDMO) selected Veeva Vault Quality to standardize its quality management processes, the first deployment was planned for a U.S. manufacturing site located on the

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Reducing Post-Acquisition QMS Integration Effort with AI 

How Assurea helped a biotechnology company assess and align site vs global QMS following an acquisition using AI-assisted analytics and expert quality review. Project Overview Following the acquisition of a biotechnology company, our client needed to understand how the acquired site’s Quality Management System (QMS) aligned with its global quality framework before beginning integration activities.

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Who Owns What in SaaS Validation? Vendor vs Regulated Company Responsibilities

Many life sciences organizations commonly ask this question when implementing a SaaS platform: “If the vendor already validated the system, what do we still need to do?” The answer is straightforward. The vendor is responsible for the platform it develops, operates, and maintains. The regulated company remains responsible for how that platform is configured, governed,

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How to Define Intended Use for AI and SaaS Tools in Pharma

Defining intended use is one of the most important steps in validating AI and SaaS tools in regulated pharma and biotech environments. The intended use statement establishes validation scope, testing strategy, risk classification, supplier oversight expectations, and procedural controls. For AI systems, this is often more difficult than traditional software because operational usage can evolve

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Validating Interfaces & Data Flows: Essential for Digital Validation in Life Sciences

In today’s digital biotech environment, labs and manufacturing sites rely on a complex network of interconnected systems: LIMS, QMS, MES, ERP, CDS, eBMRs, data historians, and analytics platforms. While each system may be validated independently, the movement of data between them is where the highest risk now lives. Regulators increasingly expect organizations to demonstrate end-to-end

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