@unpublished{kurepository50,
           title = {Comparative Rational Pharmacokinetic Modeling for Therapeutic Window Adjustment: A Computational-Analytical Framework Integrating College Algebra, Applied Calculus, and Model Selection Theory},
            note = {Unpublished},
     institution = {Keiser University Latin American Campus},
            type = {Discussion Paper},
       publisher = {Keiser University Latin American Campus, San Marcos, Nicaragua},
          author = {Borge, Kamila and Salgado, Ram{\'o}n and Zelaya, Jos{\'e}},
             url = {https://kurepository.keiseruniversity.edu.ni/id/eprint/50/},
        abstract = {This research introduces a valuable educational framework that bridges mathematical theory and applied pharmacokinetics by utilizing an analytically tractable rational model to teach model selection and parameter estimation. The study's primary strength lies in its pedagogical design: by deriving exact closed-form expressions for peak time and peak concentration, it provides an intuitive, deterministic link between parameter shifts and physiological realities, such as renal impairment. Supported by rigorous statistical diagnostics (AIC, BIC, Levenberg-Marquardt optimization) and a clever Pad{\'e}-like connection to the classic Bateman function, the authors successfully establish a transparent, FAIR-compliant learning environment. Although the framework currently relies on synthetic datasets rather than noisy, real-world clinical trials, it stands out as an exceptionally well-conceived tool for fostering quantitative literacy and model-based reasoning in STEM and pharmacology education.

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Esta investigaci{\'o}n presenta un valioso marco educativo que conecta la teor{\'i}a matem{\'a}tica con la farmacocin{\'e}tica aplicada, utilizando un modelo racional anal{\'i}ticamente manejable para ense{\~n}ar la selecci{\'o}n de modelos y la estimaci{\'o}n de par{\'a}metros. La principal fortaleza del estudio reside en su dise{\~n}o pedag{\'o}gico: al derivar expresiones exactas en forma cerrada para el tiempo pico y la concentraci{\'o}n pico, proporciona un v{\'i}nculo intuitivo y determinista entre los cambios de par{\'a}metros y las realidades fisiol{\'o}gicas, como la insuficiencia renal. Respaldado por rigurosos diagn{\'o}sticos estad{\'i}sticos (AIC, BIC, optimizaci{\'o}n de Levenberg-Marquardt) y una ingeniosa conexi{\'o}n tipo Pad{\'e} con la funci{\'o}n cl{\'a}sica de Bateman, los autores logran establecer un entorno de aprendizaje transparente y conforme a los principios FAIR. Si bien el marco actualmente se basa en conjuntos de datos sint{\'e}ticos en lugar de ensayos cl{\'i}nicos reales con ruido, se destaca como una herramienta excepcionalmente bien concebida para fomentar la alfabetizaci{\'o}n cuantitativa y el razonamiento basado en modelos en la educaci{\'o}n en ciencia, tecnolog{\'i}a, ingenier{\'i}a y matem{\'a}ticas (STEM) y farmacolog{\'i}a.},
        keywords = {Pharmacokinetic modeling; rational functions; model-based reasoning; model selection; mathematical modeling competencies; computational reproducibility; STEM education; therapeutic window. Modelado farmacocin{\'e}tico; funciones racionales; razonamiento basado en modelos; selecci{\'o}n de modelos; competencias en modelado matem{\'a}tico; reproducibilidad computacional; educaci{\'o}n STEM; ventana terap{\'e}utica.}
}