Interactive visualization of enzyme kinetics: a shiny app for biomedical, pharmacology, and biochemistry education.

Understanding enzyme kinetics is fundamental in biomedical science, pharmacology, and biochemistry, yet students often struggle to interpret kinetic models and relate them to biological function. To support learning in this area, an interactive web-based tool, the Kinetics Analysis App, was developed using the Shiny framework in R. The application enables users to input experimental or example data and compare four classical models of enzyme kinetics: Michaelis-Menten, Lineweaver-Burk, Eadie-Hofstee, and Hanes-Woolf. Real-time visualization of fitted curves and parameter estimates (Vmax and Km) allows learners to explore how model choice, data variability, and substrate concentration influence kinetic interpretation. The tool supports scaffolded, constructivist, and multimedia learning approaches, lowering mathematical barriers and encouraging hypothesis-driven exploration. Designed for integration into laboratory classes, flipped learning, or independent study, the app promotes critical thinking and enhances conceptual understanding of kinetic modeling. Informal student feedback indicates increased confidence and clarity when interpreting enzyme kinetics compared with traditional spreadsheet-based approaches. The Kinetics Analysis App therefore offers a scalable and accessible method to improve quantitative skills and deepen pedagogical engagement with enzyme kinetics.NEW & NOTEWORTHY Students often find enzyme kinetics difficult because mathematical models can appear disconnected from biological meaning. The freely available Kinetics Analysis App was created to help address this challenge. Through interactive visualization of four classical kinetic models, learners are able to explore parameter estimation and model selection in real time. This web-based tool supports active learning, improves confidence in data interpretation, and provides an accessible approach for teaching quantitative concepts in biomedical and pharmacological sciences.