Translational medicine describes the transfer of basic in vitro and in vivo data into human applications. In the light of low rates of market approvals for new medical entities, better strategies to predict the risk of drug development should be used to increase output and reduce costs. Recently, a scoring system to assess the translatability of early drug projects has been proposed. Here eight drugs from different therapeutic areas have been subjected to a retrospective test-run in this system fictively located at the phase II-III transition. The scores gained here underline the importance of biomarker quality which is pivotal to decrease the risk of the project in all cases. This is particularly evident for gefitinib. The EGFR mutation status is a breakthrough biomarker to predict therapeutic success which made this compound clinically acceptable, and this is plausibly reflected by a considerable increase of the translatability score. For psychiatric and Alzheimer's drugs, and for a CETP-inhibitor, the lack of suitable biomarkers and animal models is reflected by a low translatability score, well correlating with the excessive translational risk in these areas. These case studies document the apparent utility of the scoring system, at least under retrospective conditions, as the scores correlate with the outcomes at the level of market approval. Prospective validation is still missing, but these case studies are encouraging.