Background

The use of human genome sequenced data comes with many associated challenges. The field is highly regulated, given that datasets contain sensitive information that can lead to the identification of individuals, as well as their predisposition to diseases. Consequently, the massive collection, and use of, these types of datasets entails legal compliance risk in the fields of medical research and privacy. Currently existing solutions involve intensive labour to anonymise the data, and/or costly solutions to preserve confidentiality, and manage access on a need-to-know basis to large datasets. Lack of compliance with regulations can result in financial and reputational risks for companies.

Technology Overview

The GenoMask box is an apparatus and method for maintaining data confidentiality, by masking the genomes that provide sensitive information about an individual. It is an automated solution that anonymises the datasets, and generates a new version that can be freely used for data analysis and further research, while being compliant with regulations. It alleviates the risk of using sensitive datasets, while decreasing the cost and complex implementation of the measures that have to be in place to manage confidentiality. Our prototype comprises several computer-implemented processing elements, where the execution of genomic operations is distributed, so that sensitive information is never exposed outside of the trusted execution environment. It is a is straightforward, non-intrusive and industrially feasible solution. The current state of development is a working research prototype, running on a single board computer, that has been validated successfully in the lab.

GenoMask was created to detect sensitive sequences in reads (substrings of entire genomes), generated by next-generation sequencing machines. After identifying the portions of data that would expose sensitive information, they undergo masking, which then allows for differentiated processing, use and analysis. As a result, subsequent alignment (mapping reads in the genome) is conducted on non-sensitive information. Masked information is only recovered for alignment accuracy refinement, i.e. to verify, and, if necessary, correct the obtained position for the reads, or to get the place in case of low-accuracy alignment due to long masked parts (unaligned reads). Increased protection of sensitive genomic information enhances trust in the services offered, and aids in compliance with regulation for this type of dataset.

Benefits

(Figure 1)

Opportunity

The University is seeking direct technology licensing.

GENOMASK: an Apparatus and Method to Maintain Data Confidentiality

Patents

IP Status

Seeking