Mayo Clinic Works with TripleBlind to Streamline Diagnosis Process

We were excited this week to announce a new collaboration between TripleBlind and the Mayo Clinic. Mayo plans to use TripleBlind’s solution to validate interoperability of encrypted algorithms on encrypted data and training of new algorithms on encrypted data. Our solution will enable Mayo and other health care systems to generate insights from highly regulated data without actually accessing the data – ensuring compliance with HIPAA and other standards.

Today, health care systems have to either transfer data or algorithms outside their institution for experts to train or conduct research. This process can take many months and typically involves complicated legal contracts and a significant amount of time from technicians. Our solution eliminates this step, further protecting intellectual property.

Suraj Kapa, M.D., a practicing cardiologist and director of AI for knowledge management and delivery at Mayo Clinic, noted:

“Training novel algorithms on encrypted data sets and facilitating trust between independent parties is critical to the future of AI in medicine. By using advanced mathematical encryption technologies, we will greatly enhance scientific collaboration between groups and allow for more rapid development and scalable implementation of AI-driven tools to advance healthcare.”

TripleBlind’s advanced mathematics toolset will allow Mayo to improve the current process by enabling Mayo technicians to perform diagnostic services using data wherever it resides. The collaboration focuses on three milestones. The first milestone includes validating that an algorithm already created and “trained” at Mayo can be delivered to remote hospitals and used locally to achieve accurate diagnoses. This milestone will also demonstrate that TripleBlind’s toolset provides accurate information and effectively enforces appropriate data privacy regulations such as GDPR, HIPAA, data residency regulations and other standards.

The second milestone will demonstrate that TripleBlind’s toolset can be applied to train an algorithm that resides at Mayo to access data remotely and provide diagnostic services. The third milestone will consist of demonstrating that TripleBlind’s solution can support any type of medical data and potentially genetic data in particular. Genetic data is especially difficult to aggregate since almost by definition it is impossible to deidentify using conventional approaches.

We are eager to work together with the Mayo Clinic to assist them in providing more and better services to health care systems around the country.

This news follows TripleBlind’s recent announcement it has received funding and marketing support from Accenture Ventures, the investment arm of global professional services company Accenture (NYSE: ACN). TripleBlind is applying this funding to further refine our solution.

We wish our colleagues, partners, investors and other friends of the company the best for the holiday season. We will have another announcement highlighting our growth in early January, please check back then.

Q&A with Tom Lounibos, Managing Director of Accenture Ventures

Q. Why is Accenture Ventures interested in investing in data privacy technology?

A. Accenture Ventures is focused on cultivating emerging technologies that solve for our clients’ most critical business needs. Many global enterprises are struggling to unlock trapped value in their data and data privacy concerns, and regulatory mandates are a huge part of that. Global organizations need to be able to effectively use their data and that includes collaborating with other companies, partners and competitors. Advanced data privacy solutions close that gap.

Q. Why did you select TripleBlind?

A. TripleBlind offers a high degree of privacy and interoperability, without compromising flexibility or accuracy of the operations performed on the data. From training deep nets on images, to big data processing, TripleBlind can help capture value while enhancing compliance with global privacy regulations.

Q. What aspects of TripleBlind’s technology are unique?

A. Many companies track and monetize sensitive personal information, but doing so securely – particularly when sharing that data with other companies — is a significant challenge. TripleBlind’s approach allows enterprises to share the information and insights of their data, without sharing the data itself. This is a much more effective and elegant solution then complex contracts and other types of technologies available today.  

“TripleBlind’s approach allows enterprises to share the information and insights of their data, without sharing the data itself. This is a much more effective and elegant solution then complex contracts and other types of technologies available today. ” 

Q. In addition to providing pre-seed funding, how will Accenture Ventures support TripleBlind?

A. As part of Accenture Ventures’ Project Spotlight program, TripleBlind will get extensive access to our technology domain experience. We’ll co-innovate with them at our innovation hubs, labs and liquid studios to help them refine their product-market fit. We’ll also connect TripleBlind with other companies in the Accenture Ventures ecosystem, both to help them sell in their solutions and to create technology and distribution partnerships. In fact, TripleBlind is already talking to another Project Spotlight company we invested in this summer that has a complementary solution.

Stay Tuned! Leading Global Professional Services Company Invests in TripleBlind

In about 10 days, we will have a significant announcement. The VC arm of a leading global professional services company will invest in TripleBlind and greatly accelerate our growth by connecting us to their ecosystem of companies and expertise.

Our new investor was eager to enter the data privacy space and organized a global review of the companies in the space. After a thorough review, they chose TripleBlind, noting that our solution is much more effective than the workarounds available today – complex legal contracts, data anonymization/de-identification and cumbersome alternative technologies, such as homomorphic encryption. For an example of how our solution works, please have a look at our recent blog.

Some of the obvious problems with these workarounds include:

  • Complex legal contracts often contain terms that are limiting and/or include liability clauses that are so onerous that companies are unwilling to enter into them, thus negotiations are typically expensive and require months to complete, despite the potential collaboration benefits
  • Data anonymization/deidentification is hard to execute well. It is ineffective if it doesn’t meet three criteria: individualization (it must not be possible to identify an individual), correlation (it must not be possible to cross-check multiple data sets to identify an individual), and inference (it must not be possible to deduce information about an individual from the data set)
  • Other technologies: Homomorphic encryption is a slow process that dramatically taxes compute performance. Differential privacy introduces inaccuracies to the eventual calculation. Secure enclaves are hardware dependent, do not support AI/ML at scale, are susceptible to known hacker attacks and not easy to update.

Shortly after announcing this large investor, we plan to announce new funding by several experienced VC firms and veteran angel investors. In fact, this pre-seed round was oversubscribed.

What is generating so much interest in our solution? Today, IBM estimates that enterprises fail to utilize as much as 93% of their data to generate incremental revenue by collaborating with customers, partners and even competitors. This is typically regulated data, such as PII and PHI, or mission-critical enterprise data such as tax returns and banking transactions. Our solution enables enterprises to unlock the information and insights within this data (note I didn’t state the data itself) while remaining in compliance with GDPR, HIPAA, CCPA (California Consumer Privacy Act) and similar regulations.

At TripleBlind, we think the better answer is mathematically enforced cryptography that doesn’t rely on laws or outdated technology, but rather privacy that is built into the protocol. We are working to “build in” privacy preservation and we want to give enterprises the keys to either lock or unlock their data as they see fit.

We are excited to apply these investments to complete product development and testing, and bring our solution to the over $500 billion data analytics market.

Stay tuned for upcoming announcements of major new customers!