Adaptive information filtering is a challenging and fascinating problem. It requires the adaptation of a representation of a user’s multiple interests to various changes in them. We tackle this dynamic problem with Nootropia, a model inspired by the autopoietic view of the immune system. It is based on a self-organising antibody network that reacts to user feedback in order to define and preserve the user interests. We describe Nootropia in the context of adaptive, content-based document filtering and evaluate it using virtual users. The results demonstrate Nootropia’s ability to adapt to both short-term variations and more radical changes in the user’s interests, and to dynamically control its size and connectivity in the process. Advantages over existing approaches to profile adaptation, such as learning algorithms and evolutionary algorithms are also highlighted.