Interactive Visualisation 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–Burke, Eadie–Hofstee, and Hanes–Woolf. Real-time visualisation 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 modelling. 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.