Jane Calvert, jane.calvert@ed.ac.uk
Giovanni Stracquadanio, giovanni.stracquadanio@ed.ac.uk
This is an interdisciplinary research project focusing on the AI-driven changing nature of knowledge in biomedicine. You will be supervised by Professor Jane Calvert from the School of Social and Political Sciences and Professor Giovanni Stracquadanio from the School of Biological Sciences. You will have the opportunity to conduct research on the new UKRI Hub for Advanced Therapeutics at Edinburgh, and to collaborate with diverse partners.The project concerns the integration of AI into Cell and Gene Therapies (CGTs). Although this has been transformative – with advancements such as identifying new gene targets, optimising experimental conditions, and predicting outcomes – it also introduces greater complexity and uncertainty, challenging traditional methods of knowledge verification and validation, and potentially slowing down applications.
The overarching research question is: How could the use of AI in CGT research change the knowledge production process, and potentially challenge its progress towards applications? Sub-questions are:
1. How does and might AI change the construction and understanding of biomedical knowledge in CGTs?
2. What challenges do and might these changes pose to the verification and validation of biomedical knowledge in CGTs, and why?
3. How do and might these challenges affect the translation and application of CGT research, and how should they be addressed?
Case studies will be conducted in the Stracquadanio Lab to investigate the impact of AI at different stages of the Design-Build-Test-Learn cycle in engineering biology-driven CGT research. Ethnography and semi-structured interviews will be employed for qualitative data collection from scientists, industry partners, policymakers, and regulators, etc.
You are expected to have a theoretical background in Science and Technology Studies (STS) and Business Studies, and a good understanding of AI and Biomedicine, as well as experience in qualitative research methods and interdisciplinary analysis of complex settings. This research involves diverse stakeholders, requiring excellent networking and communication skills with academic and non-academic groups.
The project aims to identify key changes and challenges in AI integration in CGTs and propose recommendations for accelerating the translation of scientific knowledge into real-world applications. As well as the completion of a PhD thesis, it may also involve contributing to research articles, industry reports, and policy papers to disseminate findings across a wide audience.
