Interactive Pharmacokinetics: A Software for Discovery, Analysis, and Simulation

Interactive Pharmakokinetics

Abstract

Objective: We aimed to develop “interactive pharmacokinetics (PK)”, an open-source, Python-based software package with a user-friendly graphical user interface. Our main goal was to overcome the cost and complexity barriers to industry-standard PK modeling tools and to facilitate the practical application of theoretical PK principles for students and researchers.

Methods: The software employs one, two, and three-compartment models, solving systems of differential equations to simulate drug concentration-time profiles. Parameter estimation is performed using non-linear optimization algorithms to minimize the sum of squared logarithmic errors. The platform is developed in Python, using NumPy and SciPy for core computations and the multiprocessing library for parallel processing of population data.

Results: A fully integrated, functional software application with a user-friendly graphical user interface was created. The platform enables users to run simulations and visualize results, including key parameters such as C_max and T_max. It performs de novo parameter estimation from patient data for one-compartment models and generates novel two- and three-compartment models using a priori data.

Conclusion: The software provides an accessible, no-cost tool for fundamental PK simulation and modeling. It serves as both a valuable pedagogical instrument for pharmacology education and a capable platform for preliminary research, particularly in resource-limited environments. Future work should focus on comprehensive validation against established software.