By now, the scientific community not only shares a common understanding of the term big data, but is also enamoured with the sheer power of harnessing massive quantities of information. From the perspective of R&D, this new era of research can power real progress in solving difficult disease states. The most potent use of these mind-boggling datasets is likely to be in oncology. Thanks to the broad reach of the International Cancer Genome Consortium (ICGC), The Cancer Genome Atlas (TCGA) has amassed profiles of approximately 10,000 tumours. In total, the project has catalogued 10 million cancer-related mutations. All areas of cancer research have benefited from this immense undertaking.
But questions arise: once we have all this data, what do we do with it? And, as the era of big data now intersects with the era of personalised medicine, how does the life science community maximise this overlap?
As the era of big data now intersects with the era of personalised medicine, how does the life science community maximise this overlap?
Aside from the TCGA multi-year cataloguing initiative, other projects are in the pipeline to harness data-gathering and sharing. Other good quality data is available, albeit from geographically and technically disparate sources, which makes the tools and technologies that harvest meaningful information critical. How efficiently can we access, aggregate, mine and extract the right fodder for an individual workflow? Not to mention user-friendliness and the reduction of false positives and negatives. The next step is to put it all together.
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