OBJECTIVES: Stratification of oncology drug therapy by genetic marker diagnostics can reveal additional patient benefit but also might influence the development process of drug manufacturers. The objective of this study is to identify and describe the most important incentives for pharmaceutical companies to develop personalized medicine drugs. METHODS: To describe the main factors influencing the decision-making process in the development of personalized medicine drugs. The main factors influencing the process and their priority ranking were determined by structured expert interviews with pharmaceutical companies, test manufacturers and other key stakeholders such as regulatory bodies, reimbursement decision makers and payers.   RESULTS: In contrast to small companies big international companies constantly look for suitable companion diagnostic tests to select subgroups of high responder. The most important key factor for market success is the extent of clinical efficacy in comparison with competitors respectively the current treatment standard. Stratification of patient populations according to treatment response or frequency of adverse events using biomarker is regarded to increase clinical efficacy of the target indication. The test performance is important due to unsolved safety issues although not regarded as crucial for the success of the drug. In contrast to other stakeholders pharmaceutical companies did not consider personalized medicine to relevantly decrease development costs or marketing efforts respectively to increase the price potential for new drugs. A low prevalence of the remaining patient population after testing is not seen as a factor which might lead to a stop of the development of a new drug by pharmaceutical companies.   CONCLUSIONS: Genetic stratification is seen as a breakthrough in cancer therapy by pharmaceutical companies and physicians.  Due to the current need for improvement of approval and reimbursement processes for personalized medicine approaches in oncology especially in Europe future sales are more difficult to predict.