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ScienceIO leaves discretion to millions of people to structure health data – TechCrunch

Years before co-starting a stealthy business to fix the messy world of health data, Gaurav Kaushik was slowly connecting the dots on how better visualization could impact health outcomes. In 2018, the budding entrepreneur was working with a Boston-based cancer research company and FlatIron Health to see how cancer patients, their cancer mutations, and health outcomes were all linked.

Eventually, her team did an analysis that suggested that patients with triple-negative breast cancer, a severe form of cancer that particularly affects women of color, respond well to immunotherapy.

Understanding the impact of connecting unorganized patient data to treatment plans, Kaushik provided the impetus for ScienceIO, a new startup he co-founded with the CEO. Will Manidis, former member of Thiel and managing partner of the Dorm Room Fund. The startup uses natural language processing and data analytics to create a massive database of patient data that can help stakeholders better understand and treat people holistically.

“You can’t navigate without a map, and there is no map for health care. If we want to understand basic things – like which patients have urgent unmet needs and need special attention or new solutions, or find new treatments for rare diseases – it takes thousands of hours of research. work and years to discover, ”said Manidis.

Now, ScienceIO isn’t the first startup trying to fix health data. And it probably won’t be the last. The startup differentiator, however, is that it has spent years building a database of what it claims to be the most representative data.

“We’ve spent the past two years building the first healthcare AI platform of its kind. We take a data-driven approach to artificial intelligence, building the technology needed to transform disparate health data into high-quality, computable data, ”said Kaushik. “There is a tremendous opportunity to create data-driven healthcare solutions, and we are excited to see an ecosystem of businesses emerge that benefit from our platform and the [natural language processing] Renaissance.”

Natural Language Processing (NLP) is an advanced technology that makes it easier for computers to understand human speech. The company explained how NLP can be used for sentiment analysis, in which the technology examines a social media post and predicts what the human is feeling behind it. ScienceIO’s NLP app combines machine learning to find variables that impact patient health, using over 9 million medical conditions, drugs, devices, and genes as potential clues.

ScienceIO in action. Image credits: ScienceIO

Scope means that the product is applicable to a number of different potential customers. Generally speaking, for example, Kaushik believes clinicians would be able to form a more complete picture of patients based on their history.

“The patients you deal with have a litany of health issues, and it’s not enough to say that we understand your cancer very well, or that we understand socio-economic conditions independently,” Kaushik said. “It’s incredible depth on each subject and the entire patient without minimizing it. “

He added: “The reason we spent three years not talking to the world and building this dataset was to make sure that we represent the patients who are getting what a doctor should see, rather than them. reduce to their biological risks. “

Manidis gave an example that includes insurance providers, who get thousands of medical plans – and data points like bill codes, costs, terms – every day.

“You’re trying to figure out how to prioritize [claims]either to send it to arbitration or to look for things like fraud detection, ”Manidis said. “You can use ScienceIO to structure data, then understand claims and reimburse patients faster [and] More precisely.”

Notably, ScienceIO does not track, it simply makes the data more searchable and produces analyzes that can be turned into usable information. ScienceIO said it is currently in pilot programs with several clients, but declined to give specific names. The results of these pilots, according to Kaushik, will help them decide on a realistic timeline for general availability.

Progress so far has helped the once-low-key company raise an $ 8 million funding round. Investors in the cycle include institutional investors such as Section 32 and Sea Lane Ventures, as well as entrepreneurs such as Lachy Groom and Josh Buckley.