In living organisms, the pharmacological and/or toxicological effects of drugs or chemicals                  are manifested through molecular networks. A methodology that can facilitate an understanding of the molecular mechanisms underlying disease development and/or the biological alterations after treatment with drugs could be effective for use in drug discovery. Therefore, we have developed a consolidated life science information platform known as “KeyMolnet” that comprises related data and a search software. The data have been carefully selected, standardized, reviewed, and organized by our biologists. Based on the information specific to the molecules, molecular relations, pathways, diseases, and drugs, the system can generate molecular networks as required in real time. By importing experimental and/or clinical data into the KeyMolnet, researchers could obtain working hypotheses for their subsequent experiments and/or new insights into the molecular mechanisms underlying diseases and the pharmacological/toxicological actions of drugs because the information collected in KeyMolnet is combined and the molecular networks are generated based on this combined information. Particularly in the post-genome era, there has been a dramatic increase in the amount of information available with regard to life sciences, including comprehensive gene expression data. Thus, it is imperative that we exploit new technologies and methods, such as KeyMolnet and use them efficiently and effectively to the maximal extent in research. In this review, we propose new approaches to clarify the pharmacological/ toxicological mechanisms of drugs by using the molecular networks generated by KeyMolnet.