Simultant

Simultant performs simultaneous curve fitting of functions and ordinary differential equation (ODE) solutions to experimental data for parameter estimation and model-based inference.

Key Features:

• Function and ODE fitting: Supports fitting functions defined as mathematical expressions and as solutions to ordinary differential equations (ODEs).
• Analytical gradient calculations: Automatically computes analytical gradients for fitting functions, including those derived from ODE solutions, to accelerate optimization.
• Shared parameters and simultaneous fitting: Allows parameters to be shared across multiple datasets and models to enable simultaneous fitting.
• Differentiable programming: Leverages differentiable programming techniques to enable gradient-based optimization approaches.

Scientific Applications:

• Systems biology: Enables parameter estimation and model calibration for ODE-based systems biology models.
• Pharmacokinetics: Facilitates fitting of pharmacokinetic models to concentration–time experimental data.
• Nonlinear differential equation modeling: Supports modeling and parameter inference in domains involving nonlinear differential equations.
• Model validation and hypothesis refinement: Enables simultaneous model-data integration to validate predictions and refine hypotheses.

Methodology:

Integrates analytical gradient calculations with differentiable programming paradigms, computes analytical gradients for functions and ODE solutions, and supports fitting functions specified as mathematical expressions or ODE solutions with shared parameters across datasets for simultaneous optimization.