A self-directed interactive learning environment to conduct dose-response analysis

Pharmacology is an applied discipline; it combines data from carefully designed experiments with the rigours of statistical modelling. The dose-response analysis is a fundamental component of the pharmacology curriculum and an understanding of principles, methodologies and interpretation is essential for students and researchers. Pharmacokinetic/pharmacodynamic modelling is identified as a priority area by the Association of the British Pharmaceutical Industry. We developed the interactive user-friendly web-based application iDRUG (interactive Dose-Response User Guide) - an all-inclusive self-learning environment for dose-response analysis - aligning with the British Pharmacological Society (BPS) Core Curriculum. It integrates practical pharmacological techniques and detailed data analysis steps in a dose-response experiment. The availability of multiple scenarios enhances the opportunities for learners to visualise and investigate experimental data from wide-ranging pharmacological experiments that might otherwise be difficult to replicate in a standard laboratory class due to limited time, space and resources. The iDRUG application can operate as a standalone exercise or be integrated with practical activities to provide a complete and immersive experience and serves the blended approaches to teaching and learning. The application is freely available online (shiny.abdn.ac.uk/Stats/apps/iDRUG) and can be accessed and used on any browser-supported devices including tablets and smartphones meaning it is flexible, inclusive and accessible across the student community regardless of geographical location, onsite or online status. We have received positive comments from peers. We are currently working towards integrating the application with the course curriculum and conducting a survey to understand elements of iDRUG design, development, and learning experience with a variety of student cohorts. Overall, iDRUG is an innovative tool that encourages inclusive and interdisciplinary learning, with this project aligning with the international (a learning experience that is globally available), interdisciplinary (spanning pharmacology, data science and statistics), inclusive (a tool that is accessible for all) and sustainable (a future-proofed innovation).