The overarching goal of the Caladrius Project is to design and develop a ChatGPT-powered chatbot that helps medical students practice taking medical histories within the Philippine context. While similar chatbots already exist, they are usually found in developed countries such as the UK and the US. Medical simulations are still quite rare in developing countries such as the Philippines because of a lack of infrastructure such as computer hardware and Internet access. Furthermore, current versions of medical history taking are not attuned to our own cultural nuances. We therefore want to develop our own virtual patient in order to support our local languages such as Filipino, to add our cultural context, e.g., Betel nut chewing in the Northern parts of the country, and to incorporate our Ignatian value of cura personalis or care and respect for the individual person, e.g., asking how the patient is feeling instead of just focusing on the straightforward gathering of symptoms. This paper focuses specifically on how we structured the chatbot’s knowledge about the patient and the rubrics by which the medical student will be assessed. This paper discusses the design of the underlying patient database, which is at the core of the simulation. It also discusses the various technologies that will be employed to create the conversational, immersive experience. Finally, it discusses the tools that will be used to evaluate the simulation once it is deployed.