Digital twins in medicine are computational models that represent the health state of individual patients over time, enabling optimal therapeutics and forecasting patient prognosis, representing a key technology for personalised care. Many health conditions involve the immune system as an essential component, and hence, it is crucial to include its key features across spatial and temporal scales in medical digital twins. The immune response is complex and heterogeneous across diseases and patients, and its modelling requires the collective expertise of the international clinical, immunology, and computational modelling communities. A 2023 three-week workshop on immune digital twins brought together almost 100 researchers from these communities into a consortium to promote interdisciplinary collaboration and develop a detailed roadmap for immune digital twin modelling and application to be pursued over the next two years. This paper outlines the initial progress on immune digital twins achieved during the workshop and the environment that enabled effective communication between these three communities. Future steps include developing a repository of existing computational models related to the human immune system and developing infrastructure to construct complex disease models, including immune system components.