PSSC Labs Featured in Becker’s Hospital Review: Is cloud computing the best choice to handle the life sciences data avalanche?

While cloud providers are becoming more complicated and flexible, they might fall short in handling the “data avalanche” the life sciences industry is grappling with.

Data sets that are too large and complicated for traditional data processing approaches to manage are a sticky issue in the sciences, maybe no more so than in the life sciences industry. From biotechnology to pharmaceuticals to medical device makers, private-sector associations and research institutions spend their days doing research and development jobs that create terabytes of raw data gleaned from clinical outcomes, disease conditions, scientific studies, and individual patient data.

This “data avalanche” must then be sorted, analyzed, and dried into actionable data so that new drugs, biomedical instruments, and other goods can be produced, refined, tested, and accepted available as soon as possible. Due to the gravity of those decisions that rely on this info — human lives are literally at stake — life sciences companies operate under a number of their closest assessment and strictest regulations on the planet.

To deal with the data avalanche and compete in a hypercompetitive global marketplace, lots of life sciences organizations are thinking about cloud computing options to maximize their data processing capacity and storage capabilities. But, cloud options can fall short in big data processing capabilities and result in cybersecurity issues, eye-popping monthly accounts, along with other problems.

Big Data = Big Cloud Bills
Cloud providers are quick to tout the alleged cost savings of using their services over buying in-house IT infrastructure; customers do not need to come up with large capital investments upfront and pay just for what they use, even since they proceed. This works nicely for many companies, especially small start-up companies that are cash-poor and that aren’t dealing with very large data sets or highly complicated computations.

But, cloud services like AWS are notorious for sky-high monthly bills stuffed with hidden “gotchas,” particularly for companies that require a whole lot of computing power. Deep Value, which develops complicated research-driven trading algorithms, chose to run some quantities once their AWS bills began to exceed $70,000permonth. In the long run, they found that using AWS has been  380 percent more expensive  compared to buying their very own high-performance computing gear.

Besides unanticipated line items on their monthly invoice, cloud customers may also be hit hard by the indirect costs of performance problems and cyberattacks.

Cloud Performance May Not Be Up to Snuff
In the life sciences, the reliability and uptime of mission-critical systems are overriding, and a key marketing point of cloud solutions is the concept that customers don’t need to be concerned about keeping their own gear. Yet since cloud computing systems grows in popularity, cracks are appearing in its own foundation. Back in February 2017, AWS suffered an outage that was so poor, it couldn’t put into its systems to communicate with all the throngs of customers that were contested offline — due to some misconfiguration on the portion of an AWS employee.

The cloud does not necessarily beat in-house infrastructure in the operation category, possibly, particularly when processing tremendous data sets. Cloud service providers normally run several servers in different locations, which may cause quite significant latency issues when transferring large data sets and performing the highly complicated calculations that life sciences companies run all day.

The Dark Cloud of Cybersecurity Concerns
Within the last few weeks, an outbreak of AWS breaches affected organizations large and small, such as Verizon, the Republican National Committee, and a firm called Talent Pen that processed job programs containing the personal data of tens of thousands of Americans who held Top Secret security clearances. Every one of these breaches were due to the affected organizations (or their third party vendors) not having configured their AWS safety preferences correctly.

Cloud security preferences can be quite catchy, but when a company gets them correctly, they may still be hacked through no real fault of their own. Due to the precious data from so many different organizations has been migrated to the cloud, data centers have come to be highly attractive targets for hackers. Financial regulators and the tech industry are so worried about the chance of a significant attack on AWS that in the aftermath of the February outage they appeared the alarm  more than what they deem an over-reliance on the AWS service by the associations that form the bedrock of American society, especially financial companies.

The cloud safety threat to life sciences institutions is three pronged: a cyberattack that brings down their cloud may render them unable to operate; valuable market research and digital intellectual property may be stolen by competitors or foreign authorities; plus a hack may indicate running afoul of a plethora of government regulations and being struck with tens of thousands of dollars of lawsuits and fines.

In-House IT Infrastructure Approaches Optimum Customization & Control
In the end, cloud providers have problems with customization and control difficulties. When using a cloud assistance, the capability to make changes is rather limited. Services like AWS offer a menu of things that fit most organizations’ needs — unless those requirements are highly specialized. Organizations that own their own computing equipment have complete control over their data environments and may act fast to make adjustments or implement new features.

As opposed to hurrying to migrate to the cloud, certain life sciences organizations might be much better served by buying their particular high-performance computing gear to reduce their prices, enhance their cyber security, and also make the data avalanche work to allow them to accelerate production. Just a true comparison between the two can shed light on which option works best.

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