Translational science promises to deliver real benefit to the pharmaceutical industry, reducing attrition and affording high quality, efficacious medicines. The development and use of biomarkers aims to reduce drug development risks and generate a better understanding of disease. Informatics is an essential component of the translational science toolkit; researchers must be able to work effectively with biomarker data, and the capture and reuse of knowledge is vital for long-term success. An analysis of current data and knowledge management practices in the translational science area is presented.