Journals
Voice of the Editor
Professor Colleen E. Clancy, Editor-in-Chief of The Journal of Precision Medicine: Health and Disease
“The emerging field of precision education seeks to tailor learning environments and evaluations to the unique needs, trajectories, and capabilities of each learner. By leveraging digital tools to monitor engagement and performance, and by using formative feedback loops to guide student development dynamically, we are poised to move beyond one-size-fits-all assessment models toward a more responsive proactive framework to give nonjudgmental real-time feedback.”
Professor Colleen E. Clancy
Explosions in development and application of biomedical technologies and the increasingly clear relevance of individual variability in health outcomes is shifting fundamental approaches to biomedical research. Precision medicine, as both a scientific framework and a clinical necessity, constitutes a foundation on which to rethink the structure and substance of biomedical education. The teaching of physiology must evolve quickly to move beyond static established models to reflect the complex, heterogeneous and messy realities of human biology.
Historically, physiology education has centred on canonical representations of average or idealised systems. While this approach has provided clarity, consistency and strong “mental models”, it fails to capture the biological diversity and contextual sensitivity that precision medicine requires. Among the most pressing challenges is the tendency of educational curricula to resist change, so-called curricular inertia, particularly in the persistence of reductionist approaches and educational frameworks that omit variability across sex, ancestry, and molecular phenotype. The other enormous gap is in computational literacy, constituting a substantial barrier for both learners and instructors to make use of the machine learning, multiscale modelling and analyses tools for high-dimensional omics data.
In response to these challenges, we and others across the scientific community have been actively developing and testing educational interventions at the Centre for Precision Medicine at UC Davis Health. Our approach emphasises early exposure to computational tools and iterative engagement with complex systems. We have designed multiple multi-week, cohort-based programme aimed at learners across academic stages, including high school students, undergraduates, graduate and medical students, and faculty.
The curriculum is thematically structured to introduce participants to key domains of computational biomedicine. Beginning with foundational instruction in Python and C++, learners are immediately immersed in practical coding environments, even and deliberately when they have little to no prior programming experience. This immersion strategy is pedagogically intentional: by engaging students in hands-on modeling tasks before they fully grasp either the biological system or the programming syntax, we encourage cognitive flexibility, collaborative inquiry, and an authentic experience of the scientific process, a fundamental tenet of “active learning”.
Participants interact directly with practicing scientists and gain exposure to real research workflows and translational problem-solving. By the conclusion of the program, students have constructed working models, analysed experimental data, and developed computational pipelines. These are early achievements that build not only technical acumen but scientific confidence. The small-cohort format fosters deep engagement, individualised mentorship, and a culture of intellectual risk-taking. This scale of instruction allows for the testing and refinement of novel pedagogical approaches, which may ultimately inform broader curricular reforms in physiology education at large.
In parallel, we are increasingly exploring how the same principles that guide precision medicine, namely individualised profiling, real-time data integration, and adaptive intervention, can be applied to educational assessment and feedback. The emerging field of precision education seeks to tailor learning environments and evaluations to the unique needs, trajectories, and capabilities of each learner. By leveraging digital tools to monitor engagement and performance, and by using formative feedback loops to guide student development dynamically, we are poised to move beyond one-size-fits-all assessment models toward a more responsive proactive framework to give nonjudgmental real-time feedback. This is particularly relevant in complex domains like computational physiology and precision medicine where progress is often nonlinear and requires multidimensional feedback to support mastery.
As Editor-in-Chief of The Journal of Precision Medicine: Health and Disease, an editorial outlet dedicated to the advancement of precision medicine, I view these initiatives not as peripheral experiments but as central to our mission. We must train the next generation of biomedical scientists and clinicians to think at the interface of systems, data, and individuals. To do so, our educational models must be as dynamic and integrative as the science itself!
