Faculty: Pharmaceutical Sciences
Team:
- Dr. Fong Chan, Pharmacist and Assistant Professor of Teaching
- Dr. Jamie Yuen, Clinical Pharmacist and Lecturer
- Brie Weir, Manager, Educational Technology, OELTD
- Jon Paul Marchand, Director, OELTD
A team from the Faculty of Pharmaceutical Sciences shares what sparked their use of Generative AI in a teaching and learning activity—and key insights they’ve gained through this experience so far
Can you tell us about GENRx?
GENRx is a custom web-based application powered by a large language model that simulates patient interactions. It’s designed to help students practice patient interviews and physical assessments in a virtual environment. By addressing common challenges in pharmacy education—like limited space, large class sizes, and resource constraints—GENRx offers a flexible, scalable solution for repeated, low-stakes practice. Ultimately, the platform aims to build students’ confidence and competence in clinical skills by providing accessible, adaptive learning opportunities.
What motivated your team to develop GenRx?
The Faculty of Pharmaceutical Sciences has educational innovation within its strategic plan and the four of us had our own individual interests in incorporating GenAI technology into teaching and learning, which brought us together to form the GENRx team. The rapid development of GenAI technology and its potential to be applied through various use cases for pharmacy student skill development was a motivating factor. We were also inspired by other health professions adopting this technology.
The logistics of coordinating and effectively integrating patient interviewing practice in the curriculum means there are limited practice opportunities – GenAI presents an opportunity to supplement these limited in person practice opportunities with another teaching modality.
How have you engaged students in the process of learning with and through Generative AI tools?
Dr. Jamie Yuen explored Generative AI in a pharmacy course focused on team-based primary care practice. Using ChatGPT, Jamie generated patient interactions that students explored through facilitated, in-class discussions, integrating both text and voice features as the technology evolved.
This initial exploration laid the foundation for a pilot integrating an AI virtual patient with an existing case interaction platform.
With support from internal faculty funding, the project expanded to include student perspectives. Two pharmacy students joined the GENRx team, offering valuable contributions as case developers and system testers. Their work has been especially important in developing the cases, refining prompts and validating the knowledge base, enabling more realistic and effective interactions with large language models acting as virtual patients.
The project further expanded through a collaboration with the UBC Cloud Innovation Centre (CiC), where student developers have been helping create the initial prototype of the GENRx platform.
What steps have you taken to ensure students critically evaluate the outputs of AI tools?
In terms of critically evaluating outputs, pharmacy students benefit from practice – reconciling differences between patient records and interviews, or unclear communication. This doesn’t mean catching patients in an inconsistency, but the development of skills to navigate when those situations arise in a patient interview and how to approach or address it.
This learning activity benefits from the shortcomings of GenAI technology – real conversations can include ‘hallucinations’ or inconsistencies between the patient’s statements and documentation, so it’s important for students to learn how to handle those situations when they arise in practice. LLM hallucinations are one of the biggest drawbacks and barriers in implementing GenAI into teaching and learning, however, GenRX can use this drawback as a teaching point.
What opportunities or challenges have emerged when using AI tools in your teaching?
In the small pilot of our concept, there was some awkwardness navigating multiple interfaces – our prototype offers a unified interface for the patient interview and virtual simulation environment, which we hope will simplify user experience. It also doesn’t require students to draw upon previous experiences with large language models – the prompts to set up the interaction are done behind the scenes, so the students just need their patient interviewing and clinical assessment skills.
How does your use of AI align with broader trends in your faculty?
In addition to having educational innovation as a strategic pillar, Pharm Sci has a lot of staff, students, and faculty members who are interested in not just exploring ways to use AI, but also critically evaluating the use of AI in both pharmacy education and pharmacy practice.
What advice would you give to other educators interested in integrating Generative AI into their teaching and learning practices?
A great place to start is to look for places where the shortcomings of technology are an advantage in your context. This requires developing an understanding of the underlying tech, and means you aren’t fighting against it as you try and use it.
What’s are the next steps for GENRx?
We’re gearing up for the next round of development on GENRx where we will refine the platform and integrate additional functionality like a debrief, voice-to-voice interaction, and physical assessment activities. We are also preparing research and evaluation activities to capture learner and instructor perspectives and experiences of the platform to inform how the GENRx platform can enhance teaching and learning activities within the faculty. We will share these learnings with the broader UBC community. Additionally, we will be engaging in exploratory conversations with other health care discipline instructors within UBC and pharmacy instructors from other institutions to identify areas of collaboration.