Massachusetts General Hospital’s (MGH) www.massgeneral.org Neurological Clinical Research Institute (NCRI) www.ncrinstitute.org is using Big Data in novel ways to harness and interpret data sets generated from patient information.
Alex Sherman, Director of NCRI’s Center for Innovation and Biomedical Informatics explains, “The major problem is how to manage and merge information knowing that it all comes from the same person without revealing the identity of the person.”
The data comes from all different types of sources such as EEG recordings, vital signs, disease-specific measures, and medical images, tangible data from vials of biofluids and DNA samples. Information also comes from patient-reported outcomes and health statistics via mobile apps and websites.
NCRI’s use of Big Data enables researchers to learn more about rare diseases that traditionally don’t attract the attention of pharmaceutical and biotech companies. For a biotech company to take on drug development especially for a rare disease, clear biomarkers and outcome measures must be in place. Determining and validating such biomarkers requires lots of information such as clinical and phenotypical data, DNA, disease natural histories, omics, and images.
Just having the data is not enough. It is necessary for NCRI to comply with regulations, legal requirements, and laws, recommendations from governing bodies in data acquisition, curation, and importantly handling data without compromising patient privacy.
The solution is to use Neurological Global Unique Indentifiers (NeuroGUID) to securely identify patients in a research continuum. This software is able to handle patient data from numerous sources while concealing the patient’s identity. A new program was developed to allow anyone who is interested in aggregating patient-centric information to generate Neuro GUIDs and save the data using the unique identifier.
In another move, NeuroGUID’s NeuroBANK™ an online patient-centered platform helps researchers deal with the hurdles typically faced when investigating rare diseases such as ALS. The system enables the sharing and aggregation of patient data between ALS researchers and across studies. The system uses software that makes collaborations possible.
NeuroGUID’s, NeuroBANK, links data from an individual patient across multiple research projects to a variety of sources coming from medical images to genetic data to tissue repositories. This makes it possible for researchers to create their own databases and speed up the development of their studies.
To help researchers, the Department of Homeland Security’s Science and Technology (S&T) division recently awarded $5,643,466 across seven organizations to develop new tools to arm researchers with the latest insight and cybersecurity incident data to better understand and counter cyber-attacks.
To address the privacy needs especially when using medical devices, the Department of Homeland Security’s S&T program awarded MGH $950,000 https://dhs.gov/science-and-technology through the project titled “Information Marketplace for Policy and Analysis of Cyber-risk & Trust” (IMPACT) https://www.dhs.gov/csd-impact).
IMPACT supports the global cyber-risk research community by coordinating and developing real-world data and information sharing capabilities including tools, models, and methodologies. IMPACT enables data and information sharing between global academic, industry, and government cybersecurity R&D community.
The funding is going to be used to develop a medical device cybersecurity data repository through an effort titled “Healthcare Data Generation and Curation for Cybersecurity Analysis” with plans to improve cyber protection for hospital clinical environment. The information generated will enable data cybersecurity researchers to develop monitoring rule sets and tools based on changes in response to threats to medical devices and networks.