Many different resources are needed for analyzing relevant experimental data in drug design. Currently this data is difficult to access, because it is stored in heterogeneous databases, spread over many platforms, poorly interconnected, incomplete, erroneous, or just not electronically available. In order to establish a high quality database for drug design we have developed a new demand-driven methodology for integrating and semantically enriching heterogeneous data from different research areas and for migrating the data into an object-oriented database management system. In this way we have established a database containing well-prepared, relevant data needed for drug design and offering the advantages of modern database technology, like a comprehensive object-oriented data model, a flexible declarative query language and support for persistent storage and sharing of data in a multi-user environment.