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A Python module for analysis and visualization of dose-response data

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pydrc: Python Dose-Response Curves

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pydrc is a powerful Python module specially designed for the analysis and visualization of dose-response data in fields like toxicology, pharmacology, and environmental sciences.

The package simplifies the process of implementing various dose-response models, offering a uniform interface for a wide range of common models, including but not limited to Hill, Logistic, Gompertz models, and more.

Key Features

  • Wide Range of Models: Implementation of a broad selection of dose-response models.
  • Robust Estimation: Parameter estimation using state-of-the-art optimization algorithms.
  • Model Evaluation: Tools for the evaluation of model performance and selection.
  • Data Visualization: Aesthetic and intuitive visualization of dose-response curves using Matplotlib and Seaborn.
  • Flexibility: Capability to handle user-defined models.

Built for the scientific community, pydrc bridges the gap between intricate dose-response analyses and Python's ease of use, empowering researchers to concentrate on interpreting results instead of wrestling with the coding of analyses.

Contributions are welcome.

Todo

  • Implementation of multiple optimization algorithms for existing functions (Current: Levenberg–Marquardt algorithm for unconstrained optimization; Trust Region Reflective for constrained optimization)
  • Implement superfunction for data input, variable arguments and specified function to be optimized (built-in functions for now)
  • Introduce functions for effective dose estimation and benchmark dosing
  • Curve ID argument for summary table and visualization of multiple treatment groups
  • Automatic and customizable dose-response curve visualization in Matplotlib and Seaborn with **kwargs
  • Integrating and testing each function

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