AI in Focus: BlueDot and the Response to COVID-19
The next application of Artificial Intelligence (AI) to be examined in our AI in Focus series is in the area of infectious disease monitoring, which is particularly relevant during the COVID-19 pandemic.
Amid the global upheaval of COVID-19, artificial intelligence and data analytics are taking center stage for their ability to provide insights and solutions for managing the pandemic. As we discussed in an earlier article, innovative Canadian technology companies are being fueled by funding and investment opportunities and responding to urgent demands in the marketplace. Looking forward, we can expect both new AI startups, as well as existing data science companies looking to add AI technologies to their portfolio, to enter the healthcare technology space.
BlueDot’s Response to COVID-19
BlueDot, a Toronto-based digital-health company, has risen to prominence over the past seven months as an innovator in this market. On December 31st, nine days before the WHO released their first warnings about a new coronavirus, BlueDot’s technology detected unusual pneumonia cases in Wuhan, China, and alerted its clients.1 Subsequently, BlueDot correctly identified twelve of the twenty cities that would be hit following Wuhan.2 Currently, BlueDot is working with the government of Canada to monitor the spread of the virus.3
BlueDot uses big data analytics to track and anticipate the spread of infectious diseases. The company’s predictive technology works by training a computer algorithm to detect 150 pathogens from a plurality of data sources including news reports, medical bulletins, climate data, livestock reports, human population data, and more. When an unusual event is detected, the computer uses airline ticket sales data from over 4000 airports around the world to predict the spread of the disease. At this point, human experts in fields such as public health, medicine, and epidemiology take over to verify the computer’s findings and generate reports for their customers.4
A review of BlueDot’s patent portfolio reveals a strong patent strategy that positioned the company to transition from research center, to data science company, to healthcare AI leader. Multiple aspects of BlueDot’s patent strategy can be emulated by individuals and companies looking to develop or adapt their technology, including: file patent applications early, and examine your existing patent portfolio, if applicable, to determine how AI fits into your protected inventions.
Patent Filing Strategy
BlueDot’s patent strategy is characterized by early filings. BlueDot’s first patent, to a System and Method to Predict the Global Spread of Infectious Agents Via Commercial Air Travel5, claims priority to April 2, 2007: the year before Dr. Kamran Khan launched BioDiaspora, an infectious diseases research program at St. Michael’s Hospital and the predecessor to BlueDot. BlueDot’s second patent, to a Warning System for Infectious Diseases and Method Thereof6, claims priority to February 13, 2012. When Dr. Khan incorporated BioDiaspora in 2013, he would have done so with the security of one granted patent (in the US) and a second patent pending.
Further, the grant of each of BlueDot’s patents generally coincided with each of the company’s investment rounds. BioDiaspora secured seed stage funding (and changed its name) in 2014, at which point the company’s first patent was recently issued in the US. BlueDot also concluded a Series A round on August 7, 2019, at which time the company had recently received a Notice of Issue for their second patent in the US. As a result, BlueDot would have been able to assure their investors that the company was founded on novel and securely-protected technology.
When COVID-19 hit in early 2020, BlueDot did not have any US customers.7 In other words, although BlueDot filed first in the US, it took almost 13 years from its initial filing date before protection in the US became practically necessary. Nonetheless, starting the patent application process with a US provisional application was a sound forward-looking patent strategy, particularly with BlueDot being a Canadian company navigating the promise of the US market.
Scope of Protection: Data Science and AI
The scope of protection claimed in BlueDot’s patents reflects the company’s growth from a scientific research project to a leader in the healthcare AI field. The claims in the Warning System for Infectious Diseases and Method Thereof patent cover a computer system to process or model data in a global pathogen risk factors database, a global pathogen activity database, and a global transport database; detect and identify relevant data; index the relevant data; and use the indices to generate a risk indicator. Notably, the claims do not limit the scope of protection to AI; rather, the computer system can use traditional data science methods of analyzing data or AI. For example, the computer system can use machine learning algorithms taught to differentiate between “an outbreak of anthrax” and “a reunion of the heavy metal band Anthrax.”8
In July 2020, Dr. Khan noted that “BlueDot is using natural language processing (NLP) and machine learning powered by AWS to extract information on various pathogens, including location and time, and other contextual data such as case counts and deaths. The ultimate goal is to turn this unstructured text data into organized, structural spatiotemporal pathogen data, where the space and time and name of the pathogen becomes known.”9 In particular, BlueDot uses anonymous location data from hundreds of millions of mobile devices to see how the public health response to COVID-19 is working.10
It is possible that BlueDot’s use of AI is a development that occurred after filing their second patent in 2012. Nonetheless, the above analysis reveals that BlueDot’s patent claims are broad enough to protect both traditional and AI-implemented data analytics.
Conclusion
As more individuals and companies enter the healthcare technology sector, it is increasingly important that they protect their core intellectual property. BlueDot’s experience with patents, investment, and business growth illustrates the concrete benefits of filing patent applications early. Further, companies contemplating the transition from data science to AI may want to investigate whether their existing patent portfolio is adequate for the transition or whether additional AI-specific patent applications should be filed.
This has been the fifth article in our AI in Focus series. You can read the first four articles here:
- AI in Focus – Autonomous Vehicles
- AI in Focus – Fundamental Artificial Intelligence and Video Games
- AI in Focus – Robotics
- AI in Focus – Natural Language Processing
If you have any ideas for other topics that you would like us to cover in our next article in this series, please email Isi Caulder, Co-Leader of the Artificial Intelligence (AI) practice group at Bereskin & Parr LLP.
