Interview – Paul Grant, Creation Healthcare – Life Science R&D Big Data Leaders Forum 2014
Leading up to NextLevel Pharma’s 2nd Annual Life Science R&D Big Data Leaders Forum, we are conducting email interviews with selected members of our prestigious speaker panel to learn more about their thoughts on this vital issue.
*Opinions below are those only of the individual and do not reflect upon corporate strategy or positioning.
For more information regarding NextLevel Pharma’s 2nd Annual Life Science R&D Big Data Leaders Forum click here.
Paul Grant, Chief Innovation Officer, Creation Healthcare
NextLevel: What do you think makes the current Big Data challenge in Life Sciences R&D so daunting for pharma and medical device developers?
Paul Grant: Actually the Life Sciences sector has been doing 'big data' for decades, although perhaps not precisely in accordance with the hype which exists around current definitions. Therefore, it is of course important to differentiate the opportunities now afforded by high performance cloud based computing, machine learning and predictive analytics by comparison to traditional science R&D using big data sets.
We have seen how the fast-moving-consumer-goods or entertainment services sector (think Amazon, Netflix, Target etc.) have already capitalised on new streams of behavioral data which can be harvested and overlaid with existing data sets. It gives a sense of possibilities, but can be daunting for pharma and medical device developers.
The life sciences industry is unquestionably playing catch up here due to regulatory frameworks, among other things. While another industry may be able to simply upload and process data in the cloud, for regulated industries (particularly with health data), this presents a challenge. Additionally, large life sciences companies often have silos of data residing within their enterprise networks, which other divisions and departments simply have no knowledge of. Just getting to grips with where this data is and in what format can be daunting. An opportunity exists to do more with what we have already, just by implementing common sense integration across existing intelligence sources.
When it comes to R&D, I don't think we can say Life Sciences are dragging the proverbial chain; actually the opposite. I am aware of several projects using IBM Watson or Amazon AWS for example. However, my immediate and more tangible advice to industry tends to focus on understanding the customer, the stakeholder, the patient. Communication, messaging, marketing, and general stakeholder influence can and should now all be informed by big data insights. This is an era of right message, right time, right person, right place. With such an approach we can affect health outcomes, commercial performance and industry reputation.
NextLevel: Which trends have you seen on the ways in which data management and analytics are being implemented to ease the Big Data challenge?
PG: One of trends which I have personally witnessed is the change in the way medical information is shared among healthcare professionals, and indeed the number of HCPs who are using the Internet for clinical purposes rather than personal 'life-sharing'. For some companies, listening to and intercepting these signals can lead to new indications, better administration of product, or the ability to correct misinformation or confusion about products and treatments.
For the HCPs, they are simply defining and using what is available - and in some cases causing a revolution in medical education; for instance I have seen how they are self-organising their own resources and creating search engines to manage and curate what they deem to be appropriate content, currently not available through traditional means such as the manufacturers themselves.
The low-hanging fruit is to do more with any behavioral and time-based data we are already collecting. Whether that is through a rep, or a telephone contact, an email form, or website analytics, all of these 'social CRM' pieces of engagement can build to help isolate and solve problems. Big data methodologies applied to such data can bring new understanding. Let me caveat that now by saying 'big' does not necessarily mean 'better'.
To which I often quote David Spiegelhalter of Cambridge University, who once said, "There are a lot of small data problems that occur in big data. They don’t disappear because you’ve got lots of the stuff. They get worse."
NextLevel: How important do you think the big data management and analytics space is right now to enhance R&D efficiencies and break new ground?
Critical. Clearly in the R&D space we are seeing how millions of scenarios can be run on a private cloud-based cluster with significantly less investment than when a company had to cover peak load times with their own physical resource. By not focusing on architecture, hardware, and software, it releases more time and capital to explore new possibilities for science, health and decision-making.
I don't think any business leader would say 'new' big data management and analytics solutions are a replacement to other traditional ways of handling big data, although there is no doubt that it is making a difference in speed and scale, versus cost.
The other thing which is important, and changing, is the ease with which analysis can be done. Visualisation tools and programming languages are more accessible and intuitive for scientists and analysts to work with. One of my favourites of late is the language Python and the simple to maintain Anaconda package which includes many toolsets to work with data. This means the Life Sciences researcher can focus on finding or interpreting an answer, rather than spending precious mental capacity on the technology or process to getting to the answer.
Thinking on this, and other emerging software technologies, I'm interested to see how a new generation of 'digital natives' moves into this health space and whether that will provide further efficiencies, experiments, and outcomes that help the industry to advance at a more rapid pace as they do away with legacy systems and processes to 'hack' in their own way.
NextLevel: What’s the best thing for you about working in Life Sciences R&D and Data Management functions right now?
For me I would say the sense of opportunity. It seems like a new frontier where anything is possible, and once impenetrable problems can be surmounted with enough processing power. Still, I like to remember that Issac Newton did not have a supercomputer cluster, nor did Marie Curie, or the many others who have nonetheless left a legacy through their work.
Regardless of the excellent advancements in natural language processing and artificial/cognitive intelligence (such as Siri or Watson); a computer still does not conceptualise things the way a human mind can. The levels of abstraction, and association, classification, and recognition are still great strengths in the work of scientists and analysts. It is only when great minds set themselves to a problem that really game-changing solutions can be found. Sure, I'd use a smart phone calculator any day over a notepad and pen, and clearly when we are dealing with billions of records it is only through big data solutions that big data problems can be solved.
So the best thing is simply seeing how new insights can be found in the darkest corners of our data; perhaps in places where we may have stopped looking, wouldn't previously consider, or have completely forgotten about. The signal in the noise, as it were.
NextLevel: Why is this Life Science R&D Big Data Leaders Forum event a good idea for people to attend in your eyes?
Not all events are equal. Many are chiefly concerned with vendors and their wares; others are all theory and no practice. The Life Science R&D Big Data Leaders Forum is the place where leaders can convene and explore current thinking, but more importantly conceive of new paths and future possibilities through that great human trait - the spark of imagination and creativity.
I look forward to the conversations in the hallways or standing together with coffee in hand, stimulated by the presentations and great speakers. A conference is only as good as the people who attend, and the Life Science R&D Big Data Leaders Forum has so many of the key people who are pioneering thought-leadership in this space.
See you there!
For more information regarding NextLevel Pharma’s 2nd Annual Life Science R&D Big Data Leaders Forum click here.