Bringing data to life

Real-time data analytics and the drive to help patients

By Douglas Clark, M.B.A.
Senior Director, Database Strategy & Analysis, Safety and Benefit Risk Management

July 22, 2016

During a clinical trial, and also after a medicine enters the market, its efficacy and safety are continually assessed. This activity generates a lot of information and making sense of these vast amounts of data is daunting. At Biogen, we take on that “big data” challenge and turn it into a unique opportunity to improve the quality of our research and trials. My database strategy and analytics team works closely together with our safety and epidemiology groups to build advanced tools to visualize and manage this information. Our aim is to accelerate and improve decision-making with the ultimate goal of helping our patients.

Bringing data to life: the clinical and real world connection
Take a clinical trial, for example. We expect that the trial will show us whether a potential medicine is effective based on defined datasets collected from a well-defined patient population. In reality though, much more information is collected from observations at the doctor’s office or by a nurse during a home visit. This real world data includes information from electronic medical records, reports of adverse effects, patient surveys, insurance claims and even social media feeds, like Twitter and Facebook. The combination of real world data and clinical trial data provides a more comprehensive picture of how well a treatment or drug is working. We can quickly explore how often a particular safety event happens in populations ranging from very specific patients in a small trial to upwards of 100 million people.

The big question is: how do we bring all that data to life? In other words, how do we make sense of such large and diverse data sets, and how do we sift through it to tease out meaningful information? Project teams, in general, know that data will be generated, but they most likely don’t know the data (i.e., relational aspects, quality and relevance). That’s where we come in: we bridge the gap between methodology (protocol) and how to extract and interpret the information produced; we translate protocols into an analysis plan, in both plain English and in code. This can be used to better describe the characteristics of a population that we are interested in, and even help determine the risks and benefits associated with our drugs.

Staying ahead in real-time
What I find unique at Biogen is that all of these data are central to one department, Drug Safety & Benefit Risk. We work with a collaborative spirit and have cultivated strong relations with our global patient communities and end-users. Biogen has access to enormous medical claims and electronic medical record databases; two contain > 100 million patients (all patient data are de-identified and anonymous) and we’re able to respond to queries quickly. We’ve also recently launched our new Global Safety Database, the largest “cloud-based” database. This effectively harmonized global processes and our end-users can access this database in real-time.

Recently, we identified a gap in technology and developed an improved Clinical Trial Detection tool. Global Safety medical staff can now login and in real-time better analyze their data in greater detail. This is a significant upgrade over a static graph and back-and-forth conversations to get the parameters just right. We’ve completed a proof-of-concept against completed studies, and are now implementing this in on-going studies.

At Biogen, we feel like we are ahead of the game in our capabilities. The key to increasing the value of data is integration across different systems, countries, and sources of data. Our continued goal is to enable real-time access and provide data in flexible ways to streamline processes and help healthcare providers and regulators while increasing clinical trial transparency, improving patient safety and personalized treatment options for patients.

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