Biophysics and Physiological Modeling: Model Validation and Penicillin - Peter Nelson (Association of American Medical Colleges, 2010)
Abstract There is a growing movement within biology to transform the undergraduate curriculum. A major goal is to actively engage students so that they perceive biology as an evidence-based science with testable hypotheses that are supported by experimental data. This resource is the fourth module in a series that engages students in inquiry-based activities to introduce them to the process of scientific modeling and validation. The modules are a self-contained series of self-study guides for undergraduates, both with and without calculus. The modules are designed so that students can complete them without additional assistance, making them suitable for use as stand-alone biophysics computer labs or for a discovery-based active-learning course. In this module, students learn the basics of the one-compartment model of pharmacokinetics and why it predicts an exponential decay. Students compare the models predictions with experimental data for the elimination of piperacillin in healthy volunteers. During the data analysis, students discover that the fitted initial concentration predicts the distribution volume, that the fitted rate constant predicts the drug half-life, and the utility of semi-log plots. Students use graphical residual analysis to discover systematic deviations in the original fit. By reanalyzing the longer-time serum-only data, students discover that the systematic errors in the fit can be eliminated, indicating the true range of applicability of the model. This module is the fourth in a series that are being developed with the support of a National Science Foundation Course, Curriculum, and Laboratory Improvement grant. The modules are based on teaching materials I've been working on over the last 8 years for my undergraduate biophysics classes. These new courses have been developed in response to a movement within the biological sciences that calls for more quantitative content for undergraduates in biological and health sciences. I have found this module to be extremely effective in the three semesters that I have used it in my undergraduate classroom. Student engagement with the material is high as they can readily appreciate the significance of the data analyzed in the module. Students also respond well to the active-learning approach. By actually doing the fits themselves, they gain a more detailed understanding of the scientific process of model development and validation. Many have reported gaining real satisfaction in discovering new insights about the experimental results (that were not quantitatively compared with any pharmacokinetic model).