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Digital Health Trial: Can artificial intelligence predict the most optimal anti-epileptic drug?


Epilepsy, a neurological disorder characterized by unprovoked and recurrent seizures, affects 65 million people across the globe and 3.4 million in the United States. A seizure is an electrochemical storm in the brain caused by excessive and overly synchronous discharges of brain cells. Depending on what parts of the brain are involved and other factors, seizures can produce different effects. For example, small seizures may produce sensations; larger - confusion, loss of awareness and memory; even larger - falling and shaking.


Quick Facts About Seizures



Epilepsy affects about 1% of the world’s population: 65 million people, 3.4 million in US 150,000 new cases in the U.S. each year. 1 in 26 people will develop epilepsy in their lives. Two thirds of people with epilepsy get good control from medicines, while one third do not While the cause of seizures is largely unknown, more than 25 medications have been developed to help manage symptoms. The method of drug selection is still largely a matter of trial and error with over 14,000 possible combinations of up to three drugs to analyze and correlate for treatment, leaving patients suffering from severe side effects and adverse reactions, sometimes for years.

The at-home Digital Health Trial will include up to 1,000 participants from September 2019 through September 2020. Once enrolled via the doc.ai app, participants will keep an online diary tracking their seizure episodes and side effects of medication for three months. Along with the self-reported data, the study will collect and analyze patients’ health data, including an array of personal-omics information, such as the genome (DNA test provided by Kailos), phenome to capture physical traits, physiome for exercise and activity tracking, pharmacome or medication tracking and finally the exposome which includes environmental exposures. The trial also leverages doc.ai A.I. technologies such as natural language processing for participants to capture a photograph of their medication bottles for automatic import.


Epilepsy Digital Health Trial



In September 2019, doc.ai launched a new Epilepsy Digital Health Trial to explore the use of Artificial Intelligence (A.I.) in identifying the right treatment for the right patient at the right time. The study, led by principal investigator Robert Fisher, MD PhD, professor of neurology and neurological sciences at the Stanford University School of Medicine and director of the Stanford Epilepsy Center, will deploy and test A.I. to develop a predictive model for treatment.

The at-home, HIPAA-compliant and IRB-approved Digital Health Trial seeks to enroll up to 1,000 eligible participants between September 2019 and September 2020. Participants must be between 18 and 100 years old, have an epilepsy diagnosis and a smartphone using the iOS operating system, and live in the U.S. In addition to advancing epilepsy research, participants will earn rewards, which can be redeemed in the doc.ai marketplace for products and services at the completion of the trial. Interested participants can join the Epilepsy Digital Health Trial via the doc.ai app.



Once enrolled via the doc.ai app, participants will keep an online diary tracking their seizure episodes and side effects of medication for three months. Along with the self-reported data, the study will collect and analyze patients’ health data, including an array of personal-omics information, such as the genome (DNA test provided by Kailos), phenome to capture physical traits, physiome for exercise and activity tracking, pharmacome or medication tracking and finally, the exposome, which includes environmental exposures. The trial also leverages doc.ai A.I. technologies such as natural language processing for participants to capture a photograph of their medication bottles for automatic import.

“doc.ai has a robust multi-omics data pipeline, and we’re proud to contribute DNA tests free of charge to advance medicine,” said Troy Moore, Chief Scientific Officer, Kailos Genetics, Inc. “We hope to see some indications of clinical utility for DNA testing and treating someone with a variety of types of epilepsy. It’s early days, and together we’re testing a model of focused delivery to different population groups, which could strengthen links between epilepsy and genetics and show downstream outcomes.”


In partnership with the




“We’re excited to see continued advancement in the way we treat epilepsy,” said Sonya Dumanis, PhD, Senior Director of Innovation, Epilepsy Foundation. “The Digital Health Trial is another research milestone for our community as it has the potential to provide physicians and people with epilepsy with new options to optimize and personalize treatment. Our hope is that the use of A.I. to develop a predictive model to help identify the right approach for each person will help those struggling to gain better seizure control.”
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Meet Michelle Serna
I was nineteen years old when I was diagnosed with epilepsy. I will never forget the way my heart sank when my neurologist informed that there was no cure for what I was facing, only a way to moderate my seizures. Now, more than ever, as patients we are at a turning point in healthcare that is shifting treatment from the hands of practitioners to patients. People with epilepsy are not just plagued by seizures, but by the side effects of their medications – fatigue, nausea, headaches. I am incredibly excited to be joined by you and other patients that can collaborate on participating in finding a way to better our lives and the lives of the other 65 million people with epilepsy in the world. Thank you for being a part of this.
Dr. Robert Fisher MD PhD
Stanford Medicine
Scientific advisor at doc.ai
In the US, 25 medicines are available to treat epilepsy. Choosing the one to use for a particular patient often is a guessing game, resulting in failure to control seizures, side effects or both. This study will do the groundwork to train computers to more accurately use genetics and medical history to pick the best medicine. This will be a tremendous benefit for patients.
Protocol: DOC-002-2018

Using artificial intelligence to choose the optimal anti-epileptic drug

Contact us at predictepilepsy@doc.ai.

A new way of conducting research.