Indu Navar, CEO and Founder of EverythingALS, joined me to explore the roles of Artificial Intelligence, Machine Learning, and Brain Computer Interface in the search for a cure for ALS. She also shared innovative research studies on ALS detection, how Pharma can work with and support ALS patient advocates, and her key leadership lessons for digital health entrepreneurs and innovators.
Here is a sneak peek of our conversation:
Q: How can an AI or machine learning system be able to detect or predict if somebody is going to be having ALS?
A: Great question. There’s a lot of publications that’s been written on speech as one of the really good ways of figuring out neurological disorders. It’s something that AI picks up, not human beings. We can’t see any difference but it’s just that because the muscles around our vocal cord are very sensitive and it can actually make small changes.
This is data in publications, but when you have to build a real tool from it, you have to go to the next level of quality assurance. Commercializing a product is a very different beast than trying to come up with a small sample and writing a paper on it. When you take it from “Okay, you know this publication, now let’s go make it a reality.” That’s what we’re doing. We look at ourselves as commercializing these products. We work with startups that have this product and really be matched to the disease. We bring in a lot of data points and for example, with the speech, our goal was to get a thousand people – that includes people with ALS and something called PLS that only affects a certain portion, it’s not fatal because it doesn’t hit the breathing, but pretty much is the same motor neuron disease. Also included are ALS/PLS family members who might be prone to ALS because they have a higher probability.
I think the real research said, there is a 40% to 60% higher probability that you would have ALS if somebody in your family has ALS. The third is just controls. Anybody can participate, anybody who has no neurological condition. You kind of need to get all of this data set together and bring the researchers who are AI experts to come up with different modeling. The startup which we work with called Modality.AI, they have their models as well. What we do is accelerate that process, bringing in AI and machine learning ready data that can be shared with the researchers.
Just as an example, in less than six months, we were able to engage over 520 participants and our goal is to get to a thousand participants by August. These things have never been done like this before and people have never had this amount of data. When you have to take something of a quality product that goes through probably FDA approval and make that into a real product like what we are used to building in the real software world, you need to do this.
Today it does allow for us to go on social media, recruit people, bring in the data and the data infrastructure. One of the things my husband innovated is AWS at Amazon. We use a lot of the power of the cloud today to bring in a lot of the data and the ability to not only store but also compute. I think we have the technology today, we just have to get these puzzle pieces to work together so we can actually make a difference.
For more of our discussion, you can watch the whole Fireside Chat with Indu Navar, or listen to the podcast version, below.
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