IT challenges facing R&D laboratories

Neil Whitworth of Ceiba Solutions sat down with Rebecca Aris of pharmaphorum to discuss challenges facing R&D labs. He outlined the need for a specialized IT support team within the laboratory, and discussed the importance of mobile applications for data management.

Though the lab is the birthplace of discovery and innovation within an organization, it is often an overlooked environment. Scientists interact with expensive and unique equipment tied to hundreds of applications that collect innumerable types of data – foreign concepts to those outside the lab. But like anyplace else in an organization, IT support is critical within the lab environment to maintain the highly-specialized IT equipment and make sure data is handled securely and appropriately. Neil Whitworth, Vice President of Operations at Ceiba Solutions, spoke with Rebecca Aris of pharmaphorum about the IT challenges facing R&D laboratories and the value of specialized IT support teams in this space.

Interview summary

RA: Why is IT in the lab any different from IT in other parts of an organization?

NW: IT in the laboratory is extremely different from the rest of the organization due to the innate complexity of the environment. While other business units are easily serviced by IT staff trained to handle general computer issues, the lab has hundreds of applications which integrate with highly specialized and costly scientific equipment, which in turn runs on high-performance clusters. Proper management of this intricate network requires a specialized knowledge of laboratory equipment, and offers little room for error, as scientists deal with vast amounts of data to which they need uninterrupted and easy access. Because non-specialized IT teams lack the skills and training to handle the lab IT from end to end, IT support often stops at the lab door, leaving scientists to fend for themselves. As a result, the lab becomes a “no man’s land” of IT responsibility, where IT doesn’t want to interfere with anything hooked up to scientific equipment, but scientists don’t have the IT know-how to address computer issues to extract their scientific data.

“… the lab becomes a “no man’s land” of IT responsibility…”

RA: How does this impact the scientists?

NW: Scientists really want to be able to do science – they simply want things to work. From conversations we’ve had and collaborations across pharmas that we’re a part of, we know that they’re looking for ways to do more of what they do best: science, quality, and manufacturing.

A lack of IT support negatively affects the productivity of scientists, as resolving simple IT issues can dominate up to 20% of the average scientist’s day. The time scientists spend fixing their machines delays getting drugs to market and results in higher costs for both patients and drug companies. Often we see high-cost scientific equipment being underutilized or even failing mid-process because this equipment and the attached PCs are not maintained at the optimal level. Modernization is often reactive and typically occurs when machines are already worn out, while proactive preventative maintenance can be completely ignored. In my experience, it’s not uncommon to start working with a new lab and find machines running on software versions that haven’t been upgraded or patched in years.

Additionally the ability to access the vast amount of raw data generated is compromised since without true bioinformatical support, streamlining data access gets backburnered as an issue. As a result, scientists lose additional hours each week as they try to find, process and share data. This time away from core responsibilities adds to further delays in innovation and creates an environment that can be frustrating to scientists. Though hired to make discoveries, they’re forced to spend time on tasks they’re not trained to perform successfully – creating patchwork, shadow IT solutions – and pressured to make less informed decisions as data is inaccessible. This is what we call the “Lab IT Gap.”

“A lack of IT support negatively affects the productivity of scientists, as resolving simple IT issues can dominate up to 20% of the average scientist’s day.”

Pharma must evolve beyond a reactive model and adopt a truly proactive and consultative service model. This model, a lab-specialized IT support system, enables scientists to transfer IT tasks to a team that can handle them efficiently and refocus efforts on science and innovation.

RA: What does it take to transform lab IT?

NW: On a tactical level, the first step is to set up an IT support team with specialized knowledge of the laboratory environment. To evolve to a system that drives innovation the basics must first be in place –IT services must understand the complexities and processes within the lab environment, the technical idiosyncrasies of the equipment and, most importantly, be able to engage directly with vendors to manage their services proactively.

With this insight, this team is better able to partner with the scientists who need their help and are able to quickly resolve issues. Additionally, this team needs to own the IT tasks and offer strategic assistance rather than perpetuating a Break-Fix environment of shabby solutions. Over time, long-term relationships, founded on trust, can be established.

Looking at the bigger picture, we can see that one of the reasons that this is a problem in the first place is that scientists have been left on their own. A cultural divide exists between the executives whose support and budget are needed and the scientists who are struggling through their weeks. Changing this hinges on putting forth a single advocate amongst the executives who understands the differences in lab management, who can secure the required budget and organize the support within the lab.

Moving toward this change in the lab sits in parallel with an overall transformation of an organization. Management teams that understand the value of dedicated IT support teams are ones dedicated to continuing innovation and bringing new product to market. When looking for ways to drive efficiencies and cut costs, companies too often look at cutting budgets without realizing what enhancements can be made to lower costs in a beneficial way. By focusing on the start of the drug supply chain, benefits can be achieved throughout – including quicker time to market at lesser cost.

RA: If data is such a critical asset, how can so much time be lost trying to access it?

NW: Everyone in pharma knows that data is critical in the lab. Scientists use hundreds of applications and dozens of instruments to analyze and gather various pieces of data in the lab. The information drives innovation. But because of all the specialized tools and databases used, information isn’t all together. Scientists have to jump from one database to another, reference this instrument’s output and then that one’s – it’s all siloed. As they’re trying to connect the dots amongst all the data points, the best and most efficient way is to have all the data accessible via a single interface.

IT support plays a huge role in this. Lab IT support is not just about fixing the equipment. That team also needs to be able to dip into a pool of data and leverage bioinformatics specialists because sometimes the solutions are not physical or even a break-fix – rather it is about how the application is being used. In many cases, scientists are generating all the data they need but cannot access it when they really need it. The problem is often related to the architecture of storage and management of metadata. Though the problem or need comes through the IT support team, the appropriate solution may be a bioinformatics service. In such situation, it is necessary for the support team to have access to the appropriate specialists.

A strong support team can use solutions that automate delivery of key data to these scientists, which increases productivity and encourages innovation.

RA: Enterprises are facing complex data issues with BYOD. What role is that playing the lab?

NW: The next generation of science will be mobile; there’s no doubt about that. And to be honest, the industry needs to lay the groundwork for this shift now. The Lab IT Forum, which took place in February and brought together major pharmas to discuss key topics including mobility, is one way the industry is preparing. At this forum, Merck announced that it deployed Intel tablets into its lab to improve data management within a compliant environment. This has saved the company about $1 million per year. And Thermo explained that it uses tablets for remote instrument management, which improves the scientists’ productivity. The Lab of the Future, so to speak, truly adopts mobility due to the ease with which it can manage data and the support it offers, freeing up scientists to focus on science.

This really all ties back to the lab IT support team, because in the future, all laboratories will rely on this team for their data management.

RA: Thank you for your time.


About the author:

With more than 20 years’ experience in the computer industry, Neil Whitworth has proven experience in both Operations and Project management.

Neil has been a founding-shareholder in two successful IT company start-ups, in both cases managing operations within tight deadlines, high expectations, and strict budget controls – while always continuing to focus on process-innovation. At Ceiba, Neil manages all Service and Delivery functions globally.

Ceiba Solutions provides managed services, products and information analytics dedicated to helping the life sciences maximize the value of information. As the only company focused on providing high quality, onsite IT support inside the modern laboratory, its managed services offerings are uniquely positioned to help researchers maintain focus on the business of science and decision making. Ceiba’s powerful analytics and services platforms provide easy to use self-service analytics and social monitoring services designed to help customers tap the potential of the Big Data age. Ceiba’s customers include major pharmaceutical companies and world-renowned research institutions.

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