Many things have changed but much has remained the same as we have seen a dramatic increase in the generation of genetics, genomics and a variety of clinical data leading to increased data density and continued challenges in organizing and managing that data in pursuit of personalized medicine. Simultaneously, we have seen an increase in commercial and open-source solutions, and marked movement toward open sharing of tools and data in public-private partnerships, yet still few examples of traditional companion diagnostics for personalized medicine products. Most encouraging are examples of focused public and private efforts that have resulted in knowledge leading to critical assessment of existing therapies and the development of new therapies. These examples lay highly emulatable informatics foundations for rapid advances in personalized medicine.
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