This PhD project focuses on the development and evaluation of AI-powered virtual patient systems for pharmacy consultation training. The research will create sophisticated patient simulators that can interact with trainees through multiple modalities including text-based, voice, and video interfaces, providing flexible and accessible training opportunities.

Technical Development:

The core research involves designing, building and optimizing AI agents that serve as the intelligence behind virtual patients. This includes systematic investigation of agent prompt engineering, comparison of different large language models (LLMs), and fine-tuning of model parameters to achieve optimal performance. The virtual patients will be developed to represent diverse clinical conditions and patient demographics, ensuring realistic and varied consultation scenarios that reflect real-world pharmacy practice. We utilize a range of no code and low code platforms to implement our simulations, so no coding experience is required.

Evaluation Frameworks:

A critical component of the project will be the assessment of the AI systems' ability to provide appropriate, consistent, and clinically relevant responses to trainee pharmacists' questions and interactions. The evaluation will examine both the technical performance of the AI models and their educational effectiveness through a combination of quantitative and qualitative methods.

The project will also develop an innovative AI-powered assessment system capable of analysing consultation interactions and providing meaningful, personalised feedback to trainees. This tool will utilise advanced text analysis techniques alongside traditional evaluation methods such as questionnaires and surveys to assess consultation quality and learning outcomes.

Impact Assessment:

The research will conduct comprehensive studies comparing the educational effectiveness, scalability, and cost-effectiveness of AI-driven training approaches against traditional pharmacy education methods, providing evidence for the potential transformation of clinical training in pharmacy education.