Determining an Individuals’ Biology

As part of their “Healthcare Disruptive Technologies & Innovations” series, Credit Suisse hosted a small group investor dinner in March in New York City to discuss the Role of AI & Blockchain in HC Data: doc.ai Story with Walter De Brouwer, doc.ai’s Co-Founder and CEO. doc.ai is built around omics used to determine an individual’s biology. Omics includes genomics the study of genes, phenomics the study of physical traits, and exposomics, the study of environmental influences.

As doc.ai gathers and connects omics data, the app fills in knowledge gaps and advances medical science. With the progress in artificial intelligence, the ability to predict patterns across large volumes of omics data may enable a new generation of personalized medicine that is more specifically tailored to individual factors.

The company currently has 35 thousand people signed up which De Brouwer believes is enough to run some statistically meaningful trials. Individuals participating make it possible for doc.ai to have access to all their online health information including lab data, gene scan results, etc.

Individuals are able to securely collect, store, and own their data with full control of how they want their data to be used and perhaps benefit others through data research. With the use of new technology in edge learning and smartphones becoming powerful, doc.ai has been able to put the technology directly into the smartphone. Information can be stored locally and predictions can be made locally without doing the analysis in the cloud. This makes the cloud necessary only for training the model to make predictions.

The company is partnering with healthcare providers, insurers, and research institutions to offer users the opportunity to put the omics data to work to manage their own health and/or contribute to research.

Last August, doc.ai partnered with Anthem to launch an artificial intelligence data trial using blockchain. The idea was that doc.ai and advisors from Harvard Medical School would develop a framework for using machine learning to identify predictive models for allergies based upon the phenome (e.g. age, height, weight), exposome (e.g. exposure to weather/pollution based on location), and physiome (e.g. physical activity, and daily steps,) and data collected from participating Anthem employees and the public.

Anthem is a big client for doc.ai and benefits from access to much data which is beneficial in order to make the company’s engines more powerful. Separately, doc.ai is approaching Contract Research Organizations (CRO) to work with them. By the end of 2020, according to De Brouwer, people will be able to join clinical trials from their smartphones.

According to Walter De Brouwer, claims data from health insurers is superior to clinical data. He said, “Clinical data is very messy because errors often go forward since a doctor will look at what a previous doctor wrote and write a similar recap of their experience with the patient. As a result, there is no built-in process to clean up the data.”

Walter De Brouwer said, “Claims data on the other hand is curated, insurers look for inconsistencies and challenge claims because they don’t want to pay more than they should pay. This process cleans up the claims data and makes it a more reliable data set than clinical data. Pharmacy data is better than medical data, although the artificial intelligence achieved from the pharmacy data can also be achieved from the insurers’ claims data.”

Contact Jailendra Singh Research Analyst at jailendra.singh@credit-suisse.com or call (212) 325-8121 for more details or to provide feedback.

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