Pursuing a Cancer Cure with Faster Data

Jul 17, 2017
By Pharmaceutical Executive Editors

David TrossellIncreasingly, pharmaceutical companies and organizations conducting research to push cancer into history are realizing that the answer may lie in big data and in sharing it. To achieve this they need reliable network infrastructure that isn’t slowed down by the data and network latency. Even with the ever growing volumes of big data, it’s important to allow data to flow fast to permit accurate analysis.

On 27th April 2017, The Telegraph newspaper wrote: “How data is helping to select the best new cancer treatments for patients”.  The article, sponsored by Cancer Research UK, revealed: “Gifts left in wills help Dr. Bissan Al-Azikani and her team to look at vast amounts of data, which can aid them in identifying the best new cancer treatments for patients”.

Talking about her role, Dr. Bissan Al-Azikani commented: “In the past 10 years, we have made huge strides in discovering therapies as a result of understanding cancer at a molecular level. The challenge is to decide which cancer drug targets show the most promise and they should be prioritised for development. We use artificial intelligence to select the best drug targets by combining DNA data from tens of thousands of patients with billions of results from lab experiments.”

Knowledge sharing

Realizing that she can’t work as a sole beacon to find the cure for cancer, Al-Azikani has established the world’s largest cancer knowledge database (CanSAR) with Cancer Research UK’s investment. Cancer researchers can access the database free of charge. The aim is to globally democratie information to increase the odds of beating the disease. It is currently used by 170,000 researchers worldwide, and they can benefit from the fact that CanSAR offers big-picture data to enable drug discovery and to speed up the process of getting new cancer treatments to patients more quickly than they could before.

In S.A Mathieson’s ComputerWeekly article, “Genomics England exploits big data analytics to personalise cancer treatment”, Anthea Martin, Science Communications Manager at Cancer Research, explained that standard cancer treatments don’t work for everyone. This is because every individual and every cancer is different. She nevertheless argues that IT is central to testing and research —particularly as the high volumes of data present their own problems. 

This has led some of the researchers to sending hard drives to their colleagues by post. That’s neither the fastest, nor the most safe way to share data compared to sending encrypted data over a wide-area network (WAN) with the support – for example – of a data acceleration solution. This mitigates the negative effects of data and network latency, and it allows even encrypted data to be sent at speed over a WAN. It also removes the danger of losing sensitive data on hard drives or tape is removed.

Data universe

Writing for Wired magazine, Lola Dupre agreed. Her headline for her October 2016 article was “The Cure for Cancer is Data – Mountains of Data.”  She wrote: “With enough data, the theory goes, there is not a disease that isn’t druggable.” However, focusing on plunging into the depths of an individual’s DNA is not enough. She says this is because a cure for cancer requires a exabytes of data – a complete universe of it.

Without it she explained that the ability to detect patterns in a population, to apply machine learning, to find network mutations responsible for the disease is diminished. Large data sets are therefore crucial; they improve the accuracy and power of the big data analysis, and they do this to the extent that the predictors become strengthened.

Privacy and transparency

Yet there is one crucial hurdle that the researchers need to overcome: The data is not readily available, and so people need to be encouraged to share their biological data. Even in this field, data privacy is important and people will want to know that the data is being used for a good purpose. You must then convince the medical centres and genetic companies who collect this data to offer open access. Hoarding it with their own profitability in mind won’t help anyone to find a cure for cancer. Transparency is crucial, and by sharing it on an open access basis economies of scale can be attained and the data sets will number in their millions. Unfortunately, Dupre points out that the “volume of information is simply not available, but companies ranging from tech behemoths to biomedical start-ups are racing to solve these issues of scale.”

With the right digital infrastructure and informed data-sharing consent in place anything is possible. Not everyone, but many more patients may become happier in the future to share everything from the genome data to blood pressure data. With increasingly patient-friendly tests it will become possible to check each individual for signs of trouble and to act quickly. However, with the need to examine exabytes of big data, and to invest in data acceleration solutions will be a must. WAN optimization solutions and the man in the van just won’t do.

Case study

A well-known multinational pharmaceutical corporation is undergoing a modernization program. The company wants to move large amounts of data about such things as drugs trials, and other matters, across the globe in the pursuit of a cure for cancer. The type of data includes images that emanate from research labs across the globe.

At present they run an average IT infrastructure, but the business wants to move into new and exciting areas. This is Ieading to a business and IT transformation exercise, and with it the company is adopting a new approach. Traditionally, IT is often said to dictate to the business what it needs, but in this case the business is leading the change programme by informing IT what it wants and needs in order to move the data and to analyse it.  

The firm was one of the first to move into WAN optimization because it is putting data at the heart of everything it does. The business is as involved with the project as IT is. It now sees data acceleration solutions as the way forward, moving data faster to speed up their research in the hope that cure for cancer can be more quickly found. Historically it has been said that moving large volumes of their data can’t be done, but now it’s proven that it can be achieved. Although the business requires its IT infrastructure to be changed, much can be done with its existing infrastructure too with PORTrockIT.

Data acceleration solutions such as this use machine learning to increase the ability to speed up data flows. While WAN optimization is often touted by vendors as the solution, it only pays lip service to increasing data speed and as a technology it often can’t deal with encrypted data. Another aspect is that IT vendors often tout the need to replace an organisation’s existing storage and network infrastructure, but this often isn’t necessary.

For example, a larger bandwidth isn’t necessarily going to mitigate latency and solve the challenges that even cancer research organisations and pharmaceutical companies face. However, this challenge can be overcome with a new approach that is supported by artificial intelligence and machine learning to support the big data analysis. With more accurate and faster analysis it’s hope that cancer’s ability to adapt and evolve to be resistant to treatment will be eliminated.

Data roadmap

Yet IT alone won’t cure cancer. It requires a multi-disciplinary approach and a roadmap. The Association of the British Pharmaceutical Industry (ABPI), in association with management consultancy KPMG, has therefore published a “Big data roadmap”. The document examines the big data challenges with a call to action, a look at how the UK competes, and an analysis of the future big data opportunities for the pharmaceutical industry.

It concludes by saying: “We need to continue to scan the big data horizon, identifying new opportunities where innovative technologies may play an emerging role. This will ensure focused investment and contribute to a sustainable cycle – identifying and prioritizing next generation, high value opportunities.”

To create value from big data there needs to be open dialogue, and the report emphasises that collaboration is key between all of the stakeholders – say, for example, in cancer research and the use of big data to find a cancer cure. But this will amount to nothing unless the right technology is put in place to ensure that data can flow freely and fast across a WAN.

David Trossell is CEO and CTO of Bridgeworks.



Big Data Solution

I believe Big Data in the healthcare industry can be very advantageous! At LexisNexis Risk Solutions we are actively engaged in using the open source HPCC Systems data intensive compute platform along with the massive LexisNexis Public Data Social Graph to tackle everything from fraud waste and abuse, drug seeking behavior, provider collusion, disease management and community healthcare interventions. We have invested in analytics that help map the social context of events through trusted relationships to create better understanding of the big picture that surrounds each healthcare event, patient, provider, business, assets and more. For an interesting case study visit: http://hpccsystems.com/Why-HPCC/case-studies/health-care-fraud

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