Overview
improveR is the R client package for Scinteco’s improve platform - a secure, versioned repository designed specifically for pharmaceutical R&D data science and modeling workflows. This package enables seamless integration between R environments and the improve platform, providing pharmaceutical researchers with tools to manage, track, and control reproducible analytical workflows in a 21 CFR Part 11 compliant environment.
The improve platform supports comprehensive workflow management for pharmaceutical modeling (NONMEM, MATLAB, Monolix), biostatistical analysis, and data science processes, with improveR serving as the primary R interface.
Key Features
Core Functionality
- Resource Management: Load, save, and manage analytical resources with full metadata and lineage tracking
- Workflow Control: Execute and manage multi-step pharmaceutical modeling workflows
- Version Control: Built-in CLI integration for cloning, pushing, and pulling workflow changes
- Authentication: Secure OAuth-based authentication with token management
Pharmaceutical R&D Focus
- Regulatory Compliance: 21 CFR Part 11 compliant workflow tracking and documentation
- Multi-Tool Integration: Seamless integration with NONMEM, MATLAB, Monolix, SAS, and other pharmaceutical modeling tools
- Data Lineage: Comprehensive tracking of data transformations and analysis steps
- Collaborative Research: Review system for team-based pharmaceutical research
Platform Integration
improveR integrates with the broader improve platform ecosystem:
- Data Sources: Automated fetching from clinical databases and EDC systems
- Analysis Tools: NONMEM, MATLAB, Monolix, SAS integration
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Reporting: R Markdown and LaTeX report generation
- Collaboration: Team review and approval workflows
- Compliance: 21 CFR Part 11 validation and audit capabilities
About Scinteco
Scinteco is a Vienna-based technology company specializing in IT solutions for the pharmaceutical industry. The improve platform represents their commitment to providing secure, compliant, and efficient data science workflows for pharmaceutical R&D.