Herman De Prins
Chief information officer, UCB
Belgium’s UCB combines biology, chemistry and data to develop breakthrough treatments for some of the world’s most debilitating diseases. Lately, the global biopharma firm has been looking into cognitive computing and exploring how wearable smart sensors could help treat people who are living with severe neurological diseases like epilepsy. UCB’s CIO Herman De Prins explains how such tools, along with data analytics and mobile apps, could combine to transform treatment, giving doctors, for instance, real-time insight that supports treatment decisions. He believes we’re entering a new era in healthcare where data analytics could support more personalized treatment and increase the probability of success.
What’s your role in helping UCB pioneer new medical treatments?
UCB was founded in the 1920s as an industrial chemicals company, which it has since divested to focus solely on biopharmaceuticals. We focus on breakthroughs in immunological and neurological diseases. I joined five years ago with a background in heading up IT for medical device manufacturers. Making the transition to pharma was a big change for me.
In pharma, product lifecycles are much longer. For example, I recall when the first resynchronization defibrillator hit the market. New iterations appeared within a year, and even less as time went on. With biopharma, product development is a much longer process—and yet the pace of technological change is very fast. This adds a great deal of complexity to planning. You cannot say, ‘Let’s plan for 10 years out and never deviate.’ We typically look three years out, while keeping a focus on the short, medium and long term. Long-term focus would be 10 years out. I’ve learned that to innovate you need to set a clear strategy and take the collaborative approach, engaging others across the organization and tapping into the expertise of partner companies. The pace of technological change dictates this. Advancements are occurring so rapidly. The days of doing everything internally are over.
What are the biggest trends affecting your sector?
Analytics and data are transforming patient care. Analytics about real-world patient outcomes could affect how clinical trials are designed and how biopharma companies like UCB approach research and development. UCB commits 25 percent of revenues to R&D, so this is big for us. Analytics could also affect the therapy itself, for instance by giving physicians a decision-support tool that aids in diagnosis and treatment decisions. I think this is highly probable.
What’s the outlook for patients?
We’re clearly in the midst of a patient empowerment movement. Sensors, devices and mobile companion apps help enable patients to collect data that can be used to monitor and support therapies. You’re also seeing the rise of social networks like PatientsLikeMe, where patients can record how they are feeling, which reveals significantly more data that doctors could use to support treatment decisions.
One area where UCB has a strong focus is on medical innovation in immunological disorders and diseases of the central nervous system. Does data analytics play a particular role there?
Yes. For example, last year we launched a project with IBM to potentially deploy Watson with the aim of improving care for epilepsy patients. In this initiative we are exploring ways to create a predictive model to analyze real-world patient outcomes data. This model, based on predictive analytics should give us insights that eventually healthcare providers could consult at the point of care to inform their treatment decisions. You can imagine that in the future a doctor would have an app packed with evidence of real-world outcomes data or publications or something else. Cognitive computing should allow the physician to interrogate that system, comparing an individual patient’s data with all available evidence to inform possible treatment paths and increase their probability of success.
What have you learned so far?
We’ve already seen that the technology is up to the task. The computing power is already there. The barrier is a matter of getting sufficient, high-quality data. Real-world outcome data is available, but you have to ask a few essential questions: Is it clean? Is it representative of a larger group? Many hospitals have electronic medical records, but are they comprehensive? Have they captured, for example, all the data for those patients who move around or visit multiple medical facilities? Another issue is around published research. Not all of it is of equal rigor. These are challenges that must be addressed and I’m confident they will be.
Having seen cognitive computing up close, can you see it providing benefits beyond healthcare?
I see its potential in virtually all industries. Take, for example, Booking.com and travel booking sites. They already use analytics engines to deliver offers based on the data the user provides, such as past visits. They then compare that with other similar user profiles to try to predict the best packages or campaigns to offer. In industries like travel it’s even easier to put cognitive computing into use because the barriers are so low.
So why do you think healthcare is leading the way?
It’s a tool that could make sense for physicians. Specialist physicians already fine-tune their approach to therapy by comparing the latest research with their own treatment cases. Now, imagine giving physicians access to even more data and a tool to interrogate it quickly, and you expand their knowledge base. In essence, you are strengthening the physician’s capabilities as the data spell out the possible treatment options and outcome likelihoods. You are not changing the way decisions are made, per se, you are strengthening the decision process. We really are on the brink of a new era in healthcare. Part of it is being driven by a desire everywhere to reduce costs. But technology too is a driving force. Data analytics are informing new treatment solutions and that has the potential to revolutionize medicine.
UCB is also investigating the development of smart wearable sensors. How would they work for patients of neurological conditions?
Doctors tell me that there are three big challenges that typically affect treatment—and these go beyond treatment for neurological disorders. One is the ability to know whether the patient takes a drug as prescribed. Sometimes, patients do not. They might think they’re cured or they might quit after suffering unpleasant side effects. Another is the uncertainty of a specific treatment and whether it works for a patient. The ability to detect that quickly, even in real-time, can dramatically accelerate putting the patient on the best treatment path. And then there’s the issue of prevention. A big question for wearables is, can these sensors help predict an upcoming clinical event like a seizure? Right now, that’s not always the case.
We are at the early stages of wearable sensors. It is promising, but the technology has it limitations. The data collected do not give us the full picture of a patient’s condition. For example, doctors regularly collect data on a patient’s blood pressure and heart rate, and yet the data do not give us the complete picture of how the heart is performing. When dealing with neurological diseases there is further complexity. It is even more difficult for doctors to get a full, real-time view of the patient’s neurological state of health through sensors. But we believe the technology will improve dramatically. And when it does, we will see better algorithms that deliver greater insight for doctors to help their patients.
It’s surprising to hear a CIO talk so knowledgeably about the intricacies of complex medical conditions and possible treatments.
The times of a generalist IT manager—or a generalist manager, even—in an organization like ours is nearly over. I believe you have to be a specialist in your domain, whatever that domain may be. And you have to understand that that domain may change over time. On the various projects I’m involved in, I cannot sit as the CIO, speaking only of my knowledge of IT. I have to understand the disease at a sufficiently detailed level to contribute. I don’t have to be an expert. I don’t have to be a doctor, but I have to be willing to learn a bit about it and dive into the subject matter.