Diving into personalized medicine series: Star Trek, big data and protecting patient privacy | UCB
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Diving into personalized medicine series: Star Trek, big data and protecting patient privacy

Posted by
Miguel Louzan, IT Patient Value Units and Operations
At times, the rapid innovations taking place in medical technology can seem like something out of science-fiction. Remember Star Trek? The famous TV series featured, among other gadgets, a handheld device that could make an instantaneous medical diagnosis by capturing and analyzing a person’s important data.

Unwittingly, this fictional tool hinted at the promise now being realized by big data.

Today, new advances in big data technology are allowing researchers to quickly analyze and cross-reference massive sets of anonymized patient data from various sources, in order to uncover new triggers and insights that could potentially change the course of treatment for individuals and large populations living with severe diseases.

Indeed, all around us are examples of the tremendous potential of big data to accelerate innovation. Already, cognitive computing tools have been used to identify potential treatments for rare types of cancer. Groups like the American Society of Clinical Oncology (ASCO), IBM and Apple - as well as UCB - are exploring projects that seek to leverage predictive analytics to improve population health and treatment outcomes for a variety of severe diseases. Meanwhile, new wearable sensors and mobile health tools are providing us with even more insights that can help us personalize patient care.

The rise of big data has offered us unprecedented opportunity - and also, unprecedented responsibility. Unlike science-fiction, the large amounts of anonymous data needed to power these technologies are being provided by real people, and we have an obligation at all times to fiercely protect their privacy.

So how do we ensure we collect, use and protect data in an ethical way that preserves our bond of trust and collaboration with patients?

As a patient-centric company, UCB honors, believes in and supports the critical role of patient privacy in the treatment of diseases. To demonstrate such commitment, UCB has included privacy as one of the group’s core values in its Global Code of Conduct, and adopted internal rules (BCRs) to ensure data protection and privacy compliance worldwide. We will continue to go above and beyond in building trust with patients by making sure they are adequately informed of what data we collect and share, as well as offer an opportunity for patients to opt out when they choose.

It is also important for us to define the end-use of patient data before we capture it. Wearable sensors can supply us with a seemingly endless amount of data points. Our goal, however, is not merely to collect data, but to gather insights with a clear idea of which patient needs we aim to address.

By following these principles, we can use data responsibly to provide novel solutions for patients. As these technologies mature, we must develop consistent guidelines that safeguard patient privacy while allowing us to tap into the promise of big data.

What standards do you feel should be put in place in ensure we meet our patients’ expectations in the way we collect, share and protect data?

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Posted by Alexandre Grutman, 7 October 2015

Dear Miguel,
I am impressed about the level of determination of your article as well as UCB in general on how serious you are about patient data privacy.
With www.healthbank.coop, a citizen owned & controlled cooperative managing patient data, we believe we can contribute to your ambitions as they are fully aligned with ours.

Posted by Miguel Laduron, 8 October 2015

Hi Miguel,

Data privacy remains indeed crucial. Even for good causes, it should remain a key focus. SAP has developed a platform based on the in-memory data platform (Hana) allowing enhancing the research cycle and the treatment of a patient: SAP HealthLink.
Data privacy is at the earth of such a platform and actually based on the role of each player, data is fully available, partially available or anonymized, ...
Same principle are used in the CancerLinQ platform. Look at this video: https://youtu.be/6vYg2u6wvOQ
Feel free to contact me : miguel.laduron@sap.com