NovaUCD startup Empiric Logic has secured €85,000 in grant funding from Enterprise Ireland’s Innovation Partnership Programme, to develop a novel genomics data protection methodology in collaboration with the university.

Empiric Logic has developed an artificial intelligence data analysis and bioinformatics orchestration platform to simplify the exploration of human health, using genomics and other data.

The company, founded by Gareth O’Sullivan (pictured) in 2018, is based at NovaUCD and is also an Enterprise Ireland high-potential startup. The grant of €85,000 will go on a project to develop sharing of genomics data, while still providing all the necessary privacy and confidentiality protections.

According to the company, access to the right kind of high quality genomics data at scale is key to supporting advances in precision medicine. With access to the appropriate type and level of genomics data, real breakthroughs in disease diagnosis and therapy development can be achieved.

“However, genetic data by its very nature is the most personal data type attributable to an individual,” said the company. “Consequently access to and sharing of this data can only be done with consent and in accordance with data protection regulation and governance, such as GDPR, while also ensuring appropriate security and privacy controls are in place.”

In Association with

It will work with Dr Sean Ennis of the college’s school of medicine, who is director of the Academic Centre on Rare Diseases, on a project to support the sharing of genomics data while providing the necessary protections.

O’Sullivan explained: “Ensuring the privacy and security of sensitive genetic data should be a priority for companies working with this data type. However encryption, pseudonymisation and other state-of-the-art privacy and security controls might not necessarily prevent individuals from being re-identified from their genetic data.

“We aim to develop a novel and secure transform capability that will protect the data owner’s privacy, while also optimising the analysis process and incorporate this capability into our bioinformatics orchestration platform.”

Sean Ennis stated: “The methodology we are developing in this project will mean that while it will be impossible to re-identify individuals from the transformed data type, the data will however still be valuable and usable from a data analysis perspective. The data transform aspect of this approach is completely novel and currently not used anywhere.

“This methodology will protect the identity of individuals wishing to contribute their genetic data and enable greater sharing of genetic data to further support gene discovery and precision medicine-based research.”

He added that he is seeking to recruit a postdoctoral and a postgraduate researcher to join his team on the project.