Numerous practical issues must be considered when combining targeted therapies in early clinical drug development. These include tumor resistance mechanisms, the existence of multiple, redundant signaling pathways, and the failure of single-agent therapies to achieve cures. The strategies adopted to examine combinatorial therapy include the goal of hitting more than one target by specifically inhibiting signal transduction cascades and suppressing specific mechanisms of action with the use of multitargeted kinase inhibitors made possible by high-throughput screening techniques, combinatorial chemistry, and chemoinformatics. Two complex considerations are: which agents to combine given the heterogeneity of tumors and their various underlying perturbations, including secondary mutations and feedback loops, and how to translate findings from the bench to the bedside or directly from the bedside. Another consideration is: When is there enough information to provide a rationale for instituting a phase I trial? Various strategies have been used in combining molecules, including targeting diverse pathways, inhibiting upstream and downstream signals, and adopting a synthetic lethality paradigm. Other issues are: determining appropriate target populations for treatment, how to combine therapeutics with diagnostics, and the frequency of targets in patients referred to clinical trials. Here, we review these issues and we propose various novel trial designs that are logical for determining the efficacy of a drug or drug combination for personalized treatment. A difficult issue that must be answered is how many and which drugs to combine. Recent technologies, such as multiplexed assay platforms and bioinformatics, will shape the future of clinical trials and help answer these questions surrounding combinatorial treatment.