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Developing Data Strategies for the Future

Developing data strategies for the storage, analysis and protection of patient-specific data has never been more critical to the future of healthcare. Mobile applications, electronic health records, clinical data transparency, and the relative ease of genomic sequencing offer new insight into how humans respond to various treatments and environments. This data, if efficiently merged and interpreted, will drive the creation of entirely new therapies and change organizational structures.

Research and development is becoming more informed and more specific; consequently, treatments are increasingly targeted and effective and patients are demanding therapies that are unique to their situations. Biotech companies should prepare for this convergence of technology and personalized data, and develop strategies to leverage these capabilities in the future.

Within the last four months, there has been a flurry of activity around what could prove to be a revolutionary advancement in medicine. The Precision Medicine Initiative Working Group, established by the NIH in late March, has taken an active role in advancing the initiative’s goals by hosting several workshops, announcing notices for information, and unveiling a blueprint for the anticipated data management infrastructure during a recent webinar, which provides insights into the categories, sources, and uses of patient data that the NIH seeks to collect from the million-person cohort. Given this progress and promise of the approach, the initiative appears likely to further research, development, and innovation opportunities within the sector, and all life sciences companies should be positioning themselves to capitalize on the access to this unprecedented data set

Companies like 23andMe, Knome, and Omicia perform genomic sequencing to help individuals learn about their DNA. These companies also partner with large players in the biotech and pharmaceutical industry to help them research genomic data and provide analyses and reports on the information gathered.Earlier this year, 23andMe and Genentech partnered to collect data from 3,000 patients within the Parkinson’s disease community in an effort to develop more targeted therapies. 23andMe is also working with Pfizer to examine genetic factors of over 4,000 people with Inflammatory Bowel Disease.

Some companies have chosen to establish in-house departments to collect and analyze genetic data. For example, Regeneron’s Genetics Center, which was announced last year, has been conducting gene sequencing projects, exploring mouse genetics for disease modeling, and translating their discoveries to their own pipeline of products. These activities enable companies to capitalize on the trend towards precision medicine, allowing them to examine how this data can be produced and how they can leverage it to develop a more robust pipeline.

While personalized medicine on a large scale is probably years away, some life science companies, physicians, and patients can already recognize the benefits. And, as sequencing and analyzing genetic data becomes more efficient and affordable and consumers push for more customized therapies, the healthcare model of today will also need to evolve. Biotech companies should take this into consideration when developing big data analysis and protection strategies, which may include acquisitions, partnerships and creating new organizational units to prepare for the increasing availability of this genomic data.

 

Tags: Data Analytics & Insights, Data Integrity, Data Strategy
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