The current paradigm of detecting established cancer (often too late) and treating routinely with cytotoxic drugs is beginning to change. Advanced technologies such as whole genome sequencing (WGS/NGS), nanotechnology, imaging, bioinformatics and the convergence of the biological and physical sciences portends a future where personalized cancer medicine will be possible maybe even routine. However, this paradigm shift will require that a number of technical and scientific challenges be met and overcome. For example, WGS/NGS is producing multidimensional genomic and phenotypic multi-dimensional data at an unprecedented rate. Large scale genomic efforts such as The Cancer Genome Atlas are already producing multi-dimensional data sets that are unmanageable in the hands of single investigators. Cancer is quickly becoming digital information which means that we already require trained computational scientists and sophisticated analytical tools both of which are in short supply. Moreover, cancer occurs in context, so it is increasingly critical that mechanistic understanding of genomic alterations consider the cellular architecture/microenvironment in which these changes are decoded. Obviously true understanding of pathway dysfunction must also be interpreted across scales. This genomics-driven data tsunami represents major challenges on multiple fronts data quality, robust experimental design(s), standards and analysis to name a few. The massive amount of data needed to appropriately evaluate even a single patient will require teams of scientists and clinicians and large broadly available high quality data sets. Capitalizing on these opportunities for progress will require biospecimen and technology standards and appropriately qualified biomarkers developed through and end-to-end approaches that range from discovery to regulatory review. Finally, fully leveraging the outputs from the molecular sciences to both understand and control metastatic cancer will require de-convoluting the complexity of the disease. The thinking and new ideas to confront this level of complexity will likely to come from physicists, mathematicians and engineers working closely with cancer researchers. So while molecularly based medicine may well be our best strategy to date to finally defeat cancer, it is far from certain that this goal will be easily achieved or comprehensive in scope for the very complex set of diseases we collectively label cancer.