PhD Position in Generative AI in Health Technology Assessment (HTA)

How can generative AI (GenAI) support Health Technology Assessment (HTA) of medicines? HTA bodies and technology developers are already experimenting with GenAI, but systematic evidence on where it adds value and where its risks lie, is lacking. In this PhD project you will map current and future GenAI use across the full HTA lifecycle, from horizon scanning to reassessment, and translate these insights into concrete, evaluated tools for HTA assessors.

Your job
You will be on the frontline of using and implementing GenAI in the cyclic HTA approach to medicines. Possible work topics include:

• Mapping current and anticipated use of GenAI across the HTA lifecycle of medicines. This may include horizon scanning and early dialogue through initial assessment, real-world evidence generation and reassessment. You will focus on how international HTA bodies anticipate it will shape their activities in the coming years.
• Assessing the extent to which GenAI tools can reliably extract, harmonise, and analyse information from national and EU HTA reports, and identifying the conditions required to scale this across jurisdictions.
• Developing how GenAI can may link the methodological needs of HTA bodies to existing and newly developed methods, in a system that is useful in practice.
• Examining how health technology developers are using GenAI in the preparation of national and EU HTA submissions, and what this implies for how HTA bodies assess GenAI-supported submissions.

To study these questions, you will use a variety of methods, including comparative document analyses, quantitative descriptive and association studies, complex systems analyses, automated extraction data analysis and methods-needs matching

Your PhD position is part of the Academic Research Network HTA, a collaboration between the National Health Care Institute (Zorginstituut Nederland (ZIN)), Erasmus University Rotterdam, and Utrecht University (UU). The Network aims to bridge HTA research and policy by supporting specific HTA research projects closely linked to policy questions. You will work closely with other PhDs in this network and interact regularly with the HTA policy officers at ZIN. Your work will also involve close collaboration with academic experts from UU and (inter)national experts in generative AI in healthcare. Finally, you will be expected to contribute to HTA teaching for bachelor and master students.