Medicinal chemistry is a complex science that lies at the interface of many fields of research and at the very heart of drug discovery, with property relationships based on chemical structure at its core. It is clear that the effective capture and dissemination of medicinal chemistry knowledge and experience will be a key differentiator among pharmaceutical organizations and crucial for the future success in delivering effective and safe drug candidates. Therefore, in 2005 we developed ROCK (Roche medicinal chemistry knowledge), an internal user-friendly and peer-reviewed Wiki-like application to capture, browse and search tacit knowledge, key discoveries and property effects related to chemical structure, which is used as a primary source for addressing challenges faced in drug design. Drug-induced liver injury (DILI) is a leading cause of drugs failing during clinical trials and being withdrawn from the market. Comparative analysis of drugs based on their DILI potential is an effective approach to discover key DILI mechanisms and risk factors. However, assessing the DILI potential of a drug is a challenge with no existing consensus methods. We proposed a systematic classification scheme using FDA-approved drug labeling to assess the DILI potential of drugs, which yielded a benchmark dataset with 287 drugs representing a wide range of therapeutic categories and daily dosage amounts. The method is transparent and reproducible with a potential to serve as a common practice to study the DILI of marketed drugs for supporting drug discovery and biomarker development. All cells necessarily contain tens, if not hundreds, of carriers for nutrients and intermediary metabolites, and the human genome codes for more than 1000 carriers of various kinds. Here, we illustrate using a typical literature example the widespread but erroneous nature of the assumption that the ‘background’ or ‘passive’ permeability to drugs occurs in the absence of carriers. Comparison of the rate of drug transport in natural versus artificial membranes shows discrepancies in absolute magnitudes of 100-fold or more, with the carrier-containing cells showing the greater permeability. Expression profiling data show exactly which carriers are expressed in which tissues. The recognition that drugs necessarily require carriers for uptake into cells provides many opportunities for improving the effectiveness of the drug discovery process.