Semantic role labeling (SRL) is a natural language processing (NLP) task that extracts a shallow meaning representation from free text sentences. Several efforts to create SRL systems for the biomedical domain have been made during the last few years. However, state-of-the-art SRL relies on manually annotated training instances, which are rare and expensive to prepare. In this article, we address SRL for the biomedical domain as a domain adaptation problem to leverage existing SRL resources from the newswire domain.