Logo
  • Cases & Projects
  • Developers
  • Contact
Sign InSign Up

© Copyright 2025 Many.Dev. All Rights Reserved.

Product
  • Cases & Projects
  • Developers
About
  • Contact
Legal
  • Terms of Service
  • Privacy Policy
  • Cookie Policy
Development of Advanced Machine Learning-Powered Laboratory Diagnostics Software
  1. case
  2. Development of Advanced Machine Learning-Powered Laboratory Diagnostics Software

This Case Shows Specific Expertise. Find the Companies with the Skills Your Project Demands!

You're viewing one of tens of thousands of real cases compiled on Many.dev. Each case demonstrates specific, tangible expertise.

But how do you find the company that possesses the exact skills and experience needed for your project? Forget generic filters!

Our unique AI system allows you to describe your project in your own words and instantly get a list of companies that have already successfully applied that precise expertise in similar projects.

Create a free account to unlock powerful AI-powered search and connect with companies whose expertise directly matches your project's requirements.

Development of Advanced Machine Learning-Powered Laboratory Diagnostics Software

blackthorn-vision
Medical
Health & Fitness
Pharmaceuticals

Challenges in Antimicrobial Resistance Diagnostics

The global threat of antimicrobial resistance demands rapid and accurate antibiotic susceptibility testing (AST) to personalize patient therapies. Existing methods are often slow and lack the predictive power needed to combat superbugs effectively. Selux needs a robust software platform to manage its rapid AST system, integrate with existing laboratory systems, and leverage machine learning for improved diagnostic accuracy and clinical decision support.

About the Client

US-based biotechnology company revolutionizing precision diagnostics for infectious diseases with rapid antibiotic susceptibility testing.

Project Goals

  • Develop a comprehensive software platform to support Selux's Next Generation Phenotyping (NGP) System.
  • Integrate the software seamlessly with laboratory information systems (LIS) and other laboratory equipment.
  • Implement machine learning algorithms to analyze raw data and generate clinically relevant AST results.
  • Provide user-friendly interfaces for sample preparation guidance, data review, and result interpretation.
  • Ensure data security, compliance with FDA regulations, and scalability to accommodate future growth.

Functional Requirements

  • LIS Integration: Receive order requests and transmit results to/from the LIS.
  • Sample Preparation Guidance: Provide step-by-step instructions and visual aids for sample preparation.
  • Instrument Integration: Seamlessly interact with all Selux instruments (Separator, Inoculator, Analyzer).
  • Data Analysis & Machine Learning: Analyze raw data using machine learning algorithms to determine MIC values and clinical effectiveness.
  • Result Reporting & Review: Generate comprehensive result reports with clear visualizations and troubleshooting tools.
  • Administrative Tools: Provide user management, system configuration, and audit logging features.

Preferred Technologies

.NET
React
Reactquery
Axios
Styled Components
Python
Pytest
Numpy
Pandas
Scikitlearn
Miniconda
MS SQL
Google cloud SDK
GitHub
Identity Server 4
TeamCity
Jupyter
Docker
Apache Airflow

Required Integrations

  • Laboratory Information System (LIS)

Non-Functional Requirements

  • Scalability: Ability to handle increasing data volumes and user load.
  • Performance: Fast data processing and result generation times.
  • Security: Secure data storage and transmission, compliance with HIPAA and other regulations.
  • Reliability: High system availability and minimal downtime.
  • Usability: Intuitive user interface for all user roles.

Expected Business Impact

This software will enable Selux to deliver faster, more accurate, and personalized antibiotic susceptibility testing, leading to improved patient outcomes, reduced healthcare costs, and a significant impact on combating antimicrobial resistance. The improved workflows and data-driven insights will enhance lab efficiency and support clinical decision-making.

More from this Company

Secure Cloud-Based Media Content Management Platform with Real-Time Orchestration
Development of Cross-Platform Virtual Fitness Trainer Application with Adaptive Progression System
Development of Cloud-Based Business Intelligence Platform for Hospitality Industry
Development of AI-Driven No-Code Automation Platform for Enhanced Site Reliability Engineering (SRE) Workflows
AI-Powered Machine Vision Quality Control System for Industrial Automation