In this work we present a novel approach towards the extraction of factoid answers to biomedical questions. The approach is based on the combination of structured (ontological) and unstructured (textual) knowledge sources, which enables the system to extract factoid answer candidates out of a predefined set of documents that are related to the input questions. The candidates are scored by applying a variety of scoring schemes and are combined to find the best extracted candidate answer. The suggested approach was submitted in the framework of the BioASQ challenge1 as the baseline system to address the automated answering of factoid questions, in the framework of challenge 1b. Preliminary evaluation in the factoid questions of the dry-run set of the competition shows promising results, with a reported average accuracy of 54.66%.