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8 Challenges for the Biomedical Industry in terms of Big Data

We are anticipating an exponential growth in the availability of genomics big data, thank to Next-generation Sequencing (NGS) platforms that have reduced the time and cost for sequencing genomes. NIH data (see Figure 1) indicates a reduction in the cost of sequencing an entire genome from $100M in 2001 to around $1,000 in 2015. In a landmark diagnostic genomics case study in 2015, the time required to accomplish whole genome sequencing, analysis and diagnosis of genetic disease in critically ill infants was 26 hours.

Figure 1: Reduction in sequencing cost

 (Source: https://www.genome.gov/sequencingcosts/)

Is the technology partnership between the Big Data and Biomedical Industries currently positioned to support the future proliferation of genomics data? This partnership must overcome the following key challenges:

Let’s discuss a few of them:

Companies such as AWS, Oracle, and Google are positioning themselves to be the key players in forming the backbone for the biomedical companies by enabling the computational infrastructure for genomics data storage and analysis. These vendors recognize the potential value in bringing genomics research data into their platforms.

As the cost of genomic sequencing continues to shrink and sequencing on a much larger scale becomes viable, we anticipate a shift from reactionary medicine to predictive, proactive medicine. A vast genomics database will enable research leading to a better understanding of the genetics basis for a multitude of diseases.  This knowledge will spur the development of drugs and other therapies that better target disease prevention, and enable development of personal genome interpretation software that will support lifestyle counseling providing steps an individual can take to mitigate the potential impact of a disease or condition afflicting him, or to which he has a genetic disposition.

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