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Development of a Centralized Research Data Management System for Adamed
  1. case
  2. Development of a Centralized Research Data Management System for Adamed

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Development of a Centralized Research Data Management System for Adamed

impicode.com
Medical
Biotechnology
Pharmaceuticals

Challenges in Managing Heterogeneous Research Data

Adamed faces significant inefficiencies in managing vast amounts of heterogeneous research data generated across multiple departments and laboratory stages. Disparate data formats and manual documentation processes hinder regulatory compliance and slow down drug development timelines.

About the Client

A leading Polish pharmaceutical and biotech company specializing in oncology, neuropsychiatry, and diabetology research, with a global presence in over 70 countries.

Key Goals for the New System

  • Create a unified platform to aggregate research data from all stages of drug development
  • Streamline documentation processes for regulatory compliance
  • Enable seamless traceability between research stages
  • Reduce manual effort in data consolidation and reporting

Core System Requirements

  • Multi-format data ingestion from laboratory instruments and legacy systems
  • Stage-linked research data traceability
  • Automated regulatory compliance documentation
  • Collaborative workspace for cross-departmental teams
  • Advanced search and analytics dashboard

Technology Stack Preferences

Cloud-native architecture (AWS/Azure)
Microservices-based design
NoSQL databases for flexible schema
RESTful APIs for integration
React/Node.js for frontend/backend

Critical System Integrations

  • Laboratory Information Management Systems (LIMS)
  • Electronic Lab Notebooks (ELNs)
  • ERP systems for financial tracking
  • Regulatory compliance tools (e.g., FDA 21 CFR Part 11)

Non-Functional Requirements

  • High scalability for growing research volumes
  • Role-based access control with audit trails
  • 99.9% system availability SLA
  • GDPR and HIPAA compliance
  • Cross-platform compatibility with lab equipment

Expected Business Impact

The system will reduce documentation preparation time by 40-60%, improve regulatory approval success rates through standardized reporting, and enable faster iteration between research phases. It will also create a unified data repository supporting AI-driven drug discovery initiatives.

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