Sanofi and Evidation Health to work together to understand, treat disease

By Jeff Lagasse
01:33 pm
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Medicines aren’t the only tools that biopharma companies like Sanofi are using to help patients. Information technology has become a key tool in every part of Sanofi’s business, and among the most important digital tools are data and analytics; they enable the company to apply insights gained from real world evidence to the discovery, development and delivery of new medicines.
 
To advance that aspect of its digital strategy, Sanofi has strengthened its relationship with Evidation Health. The two companies will work together over the next three years to use Evidation’s Real Life study platform to help increase Sanofi’s understanding of the daily burden of disease, and develop solutions that help improve outcomes.
 
Sanofi will tap Evidation’s expertise in quantifying the impact of various real-world factors, including patient behaviors, on the eventual outcome of a course of treatment.
 
“This relationship is an important step in implementing Sanofi’s digital strategy,” Heather Bell, senior vice president and global head of digital and analytics at Sanofi, said in a statement. “One of our big priorities is to use data and analytics, and especially what we call real world evidence, to help us discover and develop better drugs, and to improve patient outcomes.”
 
Bell said the partnership will help the company better understand patient outcomes, which in turn will make them better at managing disease in a manner that reflects better value.
 
“As an example, we have already worked with Evidation Health to identify behavioral markers that could improve treatment adherence and guide positive lifestyle change in patients with type 2 diabetes,” she said.
 
The data Evidation Health is able to analyze is increasingly important, in part because of the insights it can provide to guide improved patient outcomes.
 
Healthcare professionals and research scientists have long understood that behaviors and environment can play a significant role in how people respond to medication. In some cases, those factors can even help predict how likely it is for an individual to get sick in the first place. Until recently, though, the challenge has been discovering which previously unmeasurable behaviors or circumstances are linked to a specific condition or treatment, and how significant a role they play in outcomes.
 
But as more patients become connected, the data needed for that analysis is becoming more widely available. Patient-generated information from wearables and mobile devices is growing rapidly; last year, 46 percent percent of U.S. consumers were considered active digital health adopters, while 24 percent owned a wearable and 22 percent were actively tracking at least one key health factor through a mobile app,according to a national survey conducted by Rock Health.
 
“Consumers are sharing their digital footprint through wearables, sensors and apps, and we need to listen so we can better help them navigate their day-to-day health journey,” said Christine Lemke, co-founder and president of Evidation Health, in a statement.
 
This explosion of real-world data includes both traditionally available data as well as behavioral measures like activity levels, diet, even a patient’s physical location and the local weather. Machine learning and analytics practices can pinpoint the most important of these factors, essentially creating a set of digital biomarkers that are analogous to physical biomarkers, such as blood sugar levels, that can be used to guide treatments for the best outcome.
 
Additionally, digital biomarkers can predict the onset of a condition -- for example, understanding the connection between breathing anomalies and a serious asthma attack, or correlating the decrease in a person’s frequency of social media interactions with the likelihood of an episode of severe depression.
 
“New drugs go through clinical trials to show they are safe and effective,” said Bell. “What we and the industry grapple with is how our medicines work in the real world, with real patients and physicians -- outside a carefully controlled clinical setting, where there are lots of other factors that affect their health.”

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