Genomics has a big data problem and considering that many are touting the field as the new oil, solving that problem is crucial to advancement. Sequencing the first genome cost several billion dollars and 13 years of scientists’ time, producing 200 gigabytes of raw data just to sequence a single human genome.
Cloud computing holds the key. Let’s take a look at what it’s going to take in the coming years for companies to make full use of genomics data and how they need to overcome existing hurdles.
Genomics Is Big Data
Genomics is officially a big data field. The Global Alliance for Genomics and Health predicts that over 100 million genomes will be sequenced by 2025, challenging us to the question – how do we handle that data load? Google already has a genomics storage solution, aptly named Google Genomics, as does Microsoft.
Up to now, we’ve handled it through high-performance computer clusters, which require massive capital upfront to get started and enormous maintenance costs. Only the biggest organizations can manage that kind of load, but even with enough money, upgrade costs more in downtime than is feasible for regular genomic processing.
It’s not just sequencing the genome, either. As with all data, simply having it isn’t the key. Processing it for relevant insights is what companies are after. Thorough analysis could generate another 100 gigabytes of data per genome. Traditional computing just isn’t going to cut it.
Choosing QPAIR As your Informatics Service Provider
Advancements in cloud computing have paved the way for attractive and scalable options for big data analytics. AWS has built lot of to resources help life sciences companies utilize in AWS:
Ability to scale in AWS is required to achieve high performance, rapid pipeline generation, execution and an enhanced user experience. QPAIR can get you started with bootstrapping your AWS and then automate analysis of large batches of data in AWS seamlessly.
Understanding your Shared Responsibility with AWS
Privacy and compliance concerns are particularly vexing for life science companies looking to make the switch. Privacy continues to be a significant factor in companies operating in Cloud, but there’s a big difference in the type of sensitive data in say the finance field and that of medical data. Out of the box solutions often leave out the unique needs of medical data, leaving life science companies with a lack of direction and resources.
Research companies hire their teams based on expertise within the chosen field. These teams then find themselves trying to build industry compliant solutions and maintain those solutions in the face of changing regulations and technology updates. Teams end up spending valuable time troubleshooting or workshopping ideas that never quite seem to pan out.
The truth is that few companies know how to operate in Cloud and even less, how to build the right cloud infrastructure that considers the unique compliance needs for life science industry and then how to scale their informatics.
The genome is one of the most private bits of data out there. Companies must dance the line between security and availability, presenting a highly unique issue even in the field of privacy concerns. Scientists must have the access they need to the data to provide insights into things like drug discovery and personalized medicines. Still, without forward-thinking infrastructure, that could quickly violate privacy on a fundamental level.
Many experts believe that the current obstacles to operating in Cloud are purely technical. Data analysis is getting better, and more secure, with the ability to anonymize information while allowing companies to process it still.
What companies need is a roadmap to adoption put together by experts in the unique needs of Life Science companies, yet trained to build and maintain the infrastructure research relies on. Outsourcing that solution to companies specialized in managing biotech infrastructures like QPAIR , could remove the burden from research teams, allowing them to focus on the core mission of the organization.
The Cloud will prove more critical to drug discovery and the unraveling of the genome in future years. Organizations that understand that shift will have a distinct advantage over those that insist on keeping without high-maintenance, in-house solutions. Planning ahead now could help research companies get ahead of that curve.
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