By Mark Hernon, SVP and CIO, Biogen
When you think of a pharmaceutical company or a biotech company, you think of drugs, and rightly so. But when you look behind those drugs, at what the company does on a day-to-day basis, you see that a huge amount of the business revolves around data and information. And of course, technology is a critical enabler in collecting, creating, managing and analyzing all of that data.
At Biogen, for example, one of our biggest areas of spending – hundreds of millions of dollars a year -- is on clinical trials. The output of clinical trials is data, which is then used to make decisions about the prospects of various drug candidates. Ultimately, for those candidates that move forward, all that data ends up in a submission, a filing, or an application to the U.S. Food & Drug Administration and to the equivalent health authorities in other countries.
Until that point, for all practical purposes, we are very much a technology business. Only after a drug is tested and approved does the business turn into the making of a physical product. Even then, once the drug is on the market, we continue to collect information about how effective the drug is and how it works in the real world.
Big Data keeps getting bigger
Now, as the technology continues to advance, our data use is becoming more intensive still. Today, there is much more data involved in drug development, even in the early stages. For example, there are huge volumes of genomic data that can now tell us things about how diseases progress and how it might be possible to treat those diseases. In a similar vein, when we start to identify potential drugs that could work in a certain area, where in the past you might have tested ten or 100 potential drug formulas, by leveraging technology, you can now screen thousands.
Another change is the growth in real-world data. Today, as healthcare costs grow across the world, becoming a bigger burden on governments and societies, there’s much more emphasis on demonstrating a medicine’s value not just in controlled, clinical trials but in the real world. Government drug payers want confidence that not only does the drug work but also that its economic benefits outweigh its cost. This means you don’t stop evaluating the drug at the conclusion of the clinical trials; you keep on collecting data to understand and to demonstrate the benefits that a drug or a therapy provides to patients.
Beyond simply managing that added volume, as a biotech CIO, I face two other, related challenges. One is that more and more people are tech savvy. Scientists who’ve gone through university, all the way through to PhDs, have learned to use technology to do their work. And they have preferences, they have patterns of behavior, and they have ways they like to do things.
The second challenge is the advent of things like software as a service and infrastructure as a service, which gives researchers an opportunity to try to do things for themselves rather than waiting for IT’s help. The risk is that the person who goes off and signs that software as a service contract may not be knowledgeable about information security controls and data privacy controls.
A balancing act
Finding the right balance between allowing people the flexibility and freedom to operate and maintaining control in terms of security, data privacy, and the overall level of investment in technology is a really critical part of the CIO’s job. You don’t want to squelch innovation; you don’t want to throw up barriers that would impede people’s doing their work. But at the same time, you can’t support the uncontrolled proliferation of technologies and all the risks that come with it.
The way we handle that issue here is to try to collaborate very closely with the groups that we support across the company. On my team, I have people who manage those relationships. Their role is to understand what’s happening in a particular part of the business, what that team’s needs are, how technology could help that part of the business do its work more effectively. They then collaborate with that team to develop what we call the functional roadmap for their next investments in technology over the next three to five years.
Of course, it wouldn’t be feasible to make all the investments requested by all those groups, so we have a functional steering committee to make the tough decisions. For example, within the research organization there’s a research steering committee comprising IT and research managers, and they decide the tradeoffs that need to be made. Then we repeat that whole exercise at the enterprise level, with senior executives from all the major functions. That’s where we really work through the overall company strategy and priorities.
Focusing the change
One advantage I do have as a pharma/biotech CIO is that change management is less of a problem here than in many industries. On the whole, we’re very open to change in pharma. Our bigger challenge is to channel that change, because if you take an entirely organic approach, you will have a lot of smart people pulling in different directions, and that doesn’t necessarily move the organization forward.
What do these changes mean to what it takes to be a good pharma CIO? From my point of view, the lines are blurring between what is information technology and what is business, and I think this blurring requires a different mindset, a different approach, and in many ways, a different skillset, particularly on the part of the IT people. To have a real impact on the company today, you need to be much more business savvy than once was the case. Being a technology expert in a vacuum has limited value. It’s the ability to apply that technical knowledge to real-world business challenges that really creates value for the company.
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