invivoDB: Curated Database for In Vivo Experimental Data

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A Flask-based web application for managing and analyzing in vivo experimental data, designed to support drug discovery and digital twin modeling in life sciences research.

Overview

InvivoDB provides a standardized platform for cataloging experimental animal data with structured schemas for species, therapies, experiments, and assays. The system features automated accession number generation, comprehensive data validation, and a user-friendly web interface.

Key Features

• Structured Data Management: Comprehensive models for animals, experiments, therapies, and assays
• Automated Accession Numbers: Species-specific numbering system with validation
• Therapy Classification: Categorized by mechanism of action and therapeutic approach
• Assay Integration: Support for multiple assay types with measurements and quality control
• Data Validation: Pydantic schemas ensure data integrity and API documentation
• Web Interface: Flask-based dashboard with search, filtering, and detailed views

Quick Start

Prerequisites

• Python 3.8+
• SQLite (included) or PostgreSQL for production

Installation

# Clone repository
git clone https://github.com/lujason01/invivoDB.git  
cd invivoDB

# Install dependencies
pip install -r requirements.txt

# Run the application
cd src/web
python app.py

Access the application at http://localhost:5000

Application Structure

invivoDB/
├── src/
│   ├── models/
│   │   ├── database.py     # SQLAlchemy models
│   │   └── schemas.py      # Pydantic validation schemas
│   └── web/
│       ├── app.py          # Flask application
│       ├── templates/      # HTML templates
│       └── static/         # CSS, JS, images
├── requirements.txt        # Python dependencies
└── README.md

Data Model

Core Entities:

• Species: Animal species with taxonomy information
• Animals: Individual experimental subjects with accession numbers
• Experiments: Research studies with methodology and timelines
• Therapies: Treatments categorized by mechanism of action
• Assays: Tests and measurements with quality control
• Results: Outcomes and statistical analysis

Accession Number Format: SPECIES_CODE + YEAR + SEQUENCE + CHECKSUM Example: MM2025000001A5 (Mouse, 2025, sequence 1, checksum A5)

Web Interface Pages

• Landing Page: Search-focused entry point
• Dashboard: Database statistics and recent activity
• Animals: Browse and filter experimental subjects
• Experiments: View studies with filtering by species and date
• Therapies: Categorized treatment catalog
• Assay Types: Available test methodologies
• Admin: Data management and species configuration

Configuration

Environment Variables:

• FLASK_ENV: Set to production for deployment
• SECRET_KEY: Application secret (required for production)
• DATABASE_URL: Database connection string

Default Development Settings:

• Database: SQLite (invivodb.db)
• Debug Mode: Enabled
• Port: 5000

Contributing

This project welcomes contributions from the life sciences and software development communities. Areas of focus include:

• Data standardization and validation
• API development and documentation
• Statistical analysis tools
• Integration with external databases
• Performance optimization

Team

Project Lead: Jason Lubega (@lujason01)

Novice programmer seeking mentorship and collaboration from experienced developers to advance this essential tool for life sciences research.
Full disclosure: I am usin AI tools to bring this project alive

License

Open source project - contributors welcome to showcase this work in their portfolios.

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Cheers from the invivoDB Team
Building standardized, reusable datasets for drug discovery and digital twin modeling