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Integrated Laboratory Machine Management System for Enhanced Microbiological Processing
  1. case
  2. Integrated Laboratory Machine Management System for Enhanced Microbiological Processing

Integrated Laboratory Machine Management System for Enhanced Microbiological Processing

neurosys.com
Medical
Manufacturing

Challenges in Laboratory Machine Automation and Management

A leading pharmaceutical laboratory faces difficulties in automating microbiological imaging and analysis, managing multiple complex laboratory devices, and coordinating large-scale processes across various platforms. Existing systems lack integration, flexibility, and scalable control, leading to inefficiencies and delayed processing times.

About the Client

A large pharmaceutical company specializing in microbiological testing and analysis, operating multiple laboratory machines and requiring a scalable, flexible management platform.

Goals for Improving Laboratory Operations with an Automated Management System

  • Develop a scalable and flexible software ecosystem to automate microbiological image acquisition and analysis.
  • Create dedicated applications for specific laboratory machines along with a centralized management system.
  • Enable management of multiple devices and their interactions within large-scale laboratory processes.
  • Implement user permission controls, resource allocation, and project planning functionalities.
  • Reduce system integration time and improve machinery efficiency, aiming for faster processing and higher throughput.
  • Support multi-platform compatibility to accommodate diverse operating systems used within laboratory environments.
  • Increase overall process automation, resulting in decreased manual intervention and improved analysis accuracy.

Core Functional Capabilities for Laboratory Machine Management System

  • A centralized management system for coordinating multiple devices and resources.
  • Dedicated applications for specific laboratory machines such as image acquisition, labeling, and pipetting systems.
  • An overarching control interface (e.g., a master system) to define permissions, manage user roles, and connect devices.
  • Project setup, task scheduling, and process planning functionalities for each lab machine.
  • Integration of deep learning algorithms for microbiological image analysis, detecting microorganisms and feature extraction.
  • Mechanisms for rights control, licensing, and secure user access.
  • An ecosystem architecture supporting modular development and scalability.

Recommended Technologies and Architectural Approaches

Redux for state management
Webpack and Yarn for build and package management
Material UI for frontend component design
Modular architecture supporting multi-platform deployment
Deep learning frameworks for microbiological image analysis

Necessary External System Integrations

  • Microbiological imaging systems for data acquisition
  • Laboratory devices for automation and control
  • User authentication and permission management systems
  • Data storage and analysis modules for image processing outputs

Critical Non-Functional System Requirements

  • Scalability to support increasing number of devices and data volume
  • High system availability and reliability for continuous lab operations
  • Robust security mechanisms for user permissions and data protection
  • Performance benchmarks ensuring rapid processing of microbiological images
  • Multi-platform compatibility across desktop and portable devices

Projected Business Benefits of the Laboratory Management System

Implementation of the integrated management platform is expected to significantly enhance laboratory machinery efficiency, reducing processing times and accelerating time-to-market for microbiological analyses. Target improvements include streamlining workflows, supporting multiple device management, and enabling scalable, flexible operations, ultimately boosting productivity and maintaining competitive advantage in pharmaceutical testing environments.

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