Catastrophic events occur in various fields and at various levels. Examples include earthquakes, stock market crashes, and, for individuals, the onset of diseases such as cancer.If we could understand the critical transitions (CTs) that induce catastrophes, we would be better equipped to prevent them arising or at least to mitigate their effects. Yet, despite much multidisciplinary endeavour, current tools often lack rigorous theoretical foundation and sometimes exhibit poor predictive power.The proposed research confronts this problem within a range of disciplines in the areas of clinical science, immunology, biology, and finance. Diverse approaches will be employed, including data collection (from new experiments and literature), statistical analysis, mathematical modelling, and theory development.Through synthesising the work undertaken within each discipline, the project as a whole is designed to enable the development of a more robust, generalised, interdisciplinary theory of CTs. Such theory may be used, first, to classify CTs according to their dynamics and then to provide the foundations for:a) identifying early warning signals to enable more timely, reliable, predictions of catastrophes;b) developing tools to model, analyse, and detect CTs in diverse areas of application.Ultimately, the goal of the project overall is two-fold: to support more advanced research of CTs within scientific disciplines; and, in multiple fields, to improve society’s ability to anticipate CTs to undesirable states.The proposed project entails twelve doctoral students, ten supervisors, and three external researchers. Its ambition for the students is not only to enable them to achieve more than discipline-specific expertise, but also to experience first hand the development of integrated research that a) produces cross-fertilisation between disciplines, b) synthesises empirical investigation and theoretical development, and c) combines pure and applied scientific approaches.