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Background and objective: The growing availability of patient data from several clinical settings, fueled by advanced analysis systems and new diagnostics, presents a unique opportunity. These data can be used to understand disease progression and predict future outcomes. However, analysing this vast amount of data requires collaboration between physicians and experts from diverse fields like mathematics and engineering. Methods: Mathematical models play a crucial role in interpreting patient data and enable in-silico simulations for diagnosis and treatment. To facilitate the creation and sharing of such models, the CNR-IASI BioMatLab group developed the "Gemini" (MoSpec/Autocoder) system, a framework allowing researchers with basic mathematical knowledge to quickly and correctly translate biological problems into Ordinary Differential Equations models. The system facilitates the development and computation of mathematical models for the interpretation of medical and biological phenomena, also using data from the clinical setting or laboratory experiments for parameter estimation. Results: Gemini automatically generates code in multiple languages (C++, Matlab, R, and Julia) and automatically creates documentation, including code, figures, and visualizations. Conclusions: This user-friendly approach promotes model sharing and collaboration among researchers, besides vastly increasing group productivity. [ABSTRACT FROM AUTHOR]