Transforming Argus Safety Configuration for Efficiency and Quality for a European Company

Executive Summary

A European global pharmaceutical company, set out to transform its Argus safety database configuration to ensure a more efficient, consistent, and error-resistant system for pharmacovigilance. This project aimed not only to refine technical setup but also to reimagine processes, align stakeholders, and create a sustainable roadmap for the future. Through a phased approach—Assessment & Diagnostics, Improvements & Roadmap, and Implementation—the client positioned itself to improve safety reporting accuracy and streamline compliance processes.

Background

The Argus platform is central to the client’s  safety reporting, but over time, complexity, manual steps, and inconsistent processes began to slow efficiency and introduce risks. Recognizing the need for an overhaul, the client partnered with Nextrove to review its configuration and build a future-ready solution.

Challenges

  • Complex configuration across Products, Studies, and Licenses
  • Inconsistent reporting rules and user group structures
  • Lack of a standardized maintenance approach for configuration changes
  • Potential risks from misalignment between policies, procedures, and technical setup

Solution Approach

The transformation unfolded in three phases:

1. Assessment & Diagnostics

Mapping the “as-is” state to understand all elements, from technology to people and processes. Deliverables included a detailed findings report, documented areas for improvement, and recommendations for maintaining configuration rules.

2. Improvements & Roadmap

Designing the “to-be” state with efficiency and quality in mind. The plan emphasized automation to remove manual bottlenecks, revised policies and procedures, targeted training, and a robust risk-mitigation strategy.

3. Implementation

Executing the roadmap, applying configuration changes, and embedding the new processes into daily operations.

Results

  • Greater efficiency through automation of manual steps
  • Improved data quality with consistent rule application
  • Reduced error risk by aligning technology, policies, and training
  • Future-proof roadmap enabling ongoing adaptation to regulatory changes

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