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TripleBlind Promises to Bring Data Encryption Technology to Life Sciences

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CHICAGO – Enterprise data privacy company TripleBlind plans to push further into genomics and life sciences with its proprietary encryption technology, which it says is particularly well suited for preserving the integrity of genomic sequences.

Last week, the company announced the closing of a $24 million Series A funding round, with General Catalyst and Mayo Clinic as lead investors and participation from AVG Basecamp Fund, Accenture Ventures, Clocktower Technology Ventures, Dolby Family Ventures, Flyover Capital, KCRise Fund, NextGen Venture Partners, and Wavemaker Three-Sixty Health.

Kansas City, Missouri-based TripleBlind also raised $8.2 million in March in what the firm called a pre-seed round.

TripleBlind currently serves multiple industries, including medical diagnostics, financial services, and capital markets, according to cofounder and CEO Riddhiman Das.

While the 2-year-old company, which has about 25 employees, has not disclosed any genomics or life sciences customers beyond BC Platforms, Das said it will likely have several announcements in this area in the first quarter of 2022.

In April, TripleBlind said it had partnered with BC Platforms to build a privacy-preserving, federated layer of artificial intelligence for the Swiss firm's BCRquest.com global network of biobanks.

For that partnership, TripleBlind is supplying its encryption technology for multiomic data analysis and results delivery within the framework of BCRquest.com, which supplies research cohorts for pharmaceutical R&D.

BC Platforms said at the time that it needs the TripleBlind technology to safeguard data as part of its participation in the Privacy Preserving AI for Synthetic and Anonymous Health Data consortium, a two-year project to encourage Finnish companies to promote access to and share health information. Switzerland-based BC Platforms runs its research and development out of Espoo, Finland.

As part of the new Mayo investment, John Halamka, president of Mayo Clinic Platform, has joined the TripleBlind board as an observer. Mayo Clinic Platform is the health system's artificial intelligence-centric partnership with Google to improve healthcare delivery through digital health technologies.

"Bringing together AI algorithms and data in ways that preserve privacy and intellectual property is one of the keys to delivering the next generation of digital medicine," Halamka said in a statement issued by TripleBlind. "These novel privacy-protected solutions promise to usher [in] a new era of collaboration."

However, Halamka, the former longtime CIO of Beth Israel Deaconess Medical Center in Boston, said in an email that Mayo Clinic Platform is still evaluating TripleBlind and has not deployed the technology for any genomic or clinical purposes.

Das said that TripleBlind will serve as the "trust layer" that enables secure development on the Mayo Clinic Platform.

For its part, TripleBlind is intent on preserving the accuracy of data, a particularly important consideration in genomics, Das said.

More traditional encryption techniques like tokenization or hashing are inadequate for genomics, he said, because they introduce noise into the genetic sequence. All these methods do is allow scientists to distinguish between datasets, not to compute the data, he said, which is what TripleBlind wants to enable.

The company, on the other hand, performs one-way encryption for one-time use by a single algorithm or computing operation. One-way encryption means the data is encrypted but not decrypted. Decryption renders the data as it originally was, which is great until someone shares the decrypted information, which creates a security risk.

Das gave the example of encrypted email. Once the recipient decrypts a message, the information is regenerated in its original form. "When I transmit data to you, I have lost the ability to now enforce how the data is going to be used," Das explained. "You can print it, forward it, copy it, do whatever you want with it."

With TripleBlind's one-way encryption, a data file like a genetic sequence can only be used for explicitly authorized purposes within an encrypted space. "TripleBlind's innovation is the ability to run any algorithm on any data while the data stays encrypted," Das explained. "You don't run the risk of potential reidentification ever of a patient. It is mathematically impossible to use that encrypted data and cross-correlate that with other datasets and try to narrow down who you might be," Das said.

Users can also opt to encrypt the algorithm that computes the data in this secure environment. This helps organizations protect their intellectual property.

"You can license your prostate cancer algorithm that may have cost a lot in R&D anywhere in the world with the guarantee that it will never be able to be used in a way that would reveal the inner workings of it," Das said.

Das expects TripleBlind to help bridge the divide between genomics and medical diagnostics because it is important for algorithm development to have diverse datasets. This can improve clinical applications as well as therapeutic discovery, he said.

On the therapeutic side, Das said that his company's technology provides clinical trial administrators with early indications whether or not a trial is trending in the right direction, while also protecting the double-blind nature of those investigations.

The firm is also helping with the validation of algorithms submitted for regulatory review while safeguarding intellectual property. This could be particularly useful for US companies seeking CE marking in Europe, according to Das.

It could also help with the transfer of data from Europe to the US. In 2020, the Court of Justice of the European Union invalidated the mechanism for transferring data from the European Economic Area to private companies in the US that had self-certified to the US Department of Commerce via a framework called Privacy Shield to ensure data protection. Das said that TripleBlind technology allows US-based entities to process European data without violating this ruling, known as Schrems II.

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