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In the past decade chemical and biological laboratory experiments have generated an explosive amount of data. As a result, a set applications that manipulate these dynamic, heterogeneous and massive amounts of data have emerged. An example of such applications in the pharmaceutical industry is the computational process involved in the early drug discovery of lead drug candidates for a given target disease. The discovery of lead drug candidates requires both consecutive and random data access to the pharmaceutical drug candidate database. This paper focuses on performance enhancement techniques for the pharmaceutical drug candidate database application. In particular, this paper compares static load balancing and dynamic load balancing in the context of the drug candidate database application. This database application is based on multi-queries. Some of these queries are multi-join queries.